The tumor stroma was destroyed (the number of CAFs was reduced by 98%), intratumoral hemorrhage developed, and the level of acidity within the TME was reduced. Further, no tumors developed in 20 out of 25 tumor-free mice re-challenged by an additional injection of cancer cells. The therapeutic effect on CT26 tumors was insignificant in nude mice, lacking T-cells. Thus, targeted delivery of STINGa to tumor stroma and TAMs induces activation of signaling, potentially resulting in the recruitment and infiltration of T-cells, which gain access to the tumor core. The cytotoxic activity of T-cells is not impaired by an acidic environment and immune memory is developed.Despite significant progress in the development of novel STING agonists (STINGa), applications appear to be challenged by the low efficiency and poor selectivity of these agents. A pH Low Insertion Peptide (pHLIP) extends the lifetime of a STINGa in the blood and targets it to acidic cancer-associated fibroblasts (CAFs), tumor-associated macrophages (TAMs), myeloid derived suppressor cells (mMDSCs) and dendritic cells (DCs). CAFs constitute 25% of all live cells within CT26 tumors, and M2-type TAMs and mMDSCs are the most abundant among the immune cells. The resulting activation of cytokines within the tumor microenvironment (TME) triggers the eradication of small (100 mm Immune evasion is a hallmark of cancer. Overcoming that evasion to harness the power of the immune system to attack tumors has become a widely employed strategy , 2. In rA diABZI STING agonist was modified with a linker to prepare o-pyridyl-dithioethyl-carbamoyl-PAB-STING (Pys-PAB-STINGa). The agent was synthesized and purified by Iris Biotech GmbH. All pHLIP peptides used in the study were synthesized and purified at CSBio. For conjugation with Pys-PAB-STINGa the following pHLIP sequences with single Cys residues at the membrane-inserting ends of the peptides were used:pHLIP(Laa): ADDQNPWRAYLDLLFPTDTLLLDLLWCG consisting of all L amino acids andpHLIP(Daa): ADQDNPWRAYLDLLFPTDTLLLDLLWCG consisting of all D amino acids.ε322 = 46,200 M−1cm−1, for ICG-pHLIP-STINGa ε800 = 137,000 M−1cm−1 and for Al647-pHLIP-STINGa ε651 = 270,000 M−1cm−1.pHLIP peptides and Pys-PAB-STINGa were mixed in dimethyl sulfoxide (DMSO) at a molar ratio 1:1. Sodium phosphate buffer (100 mM) containing 150 mM NaCl at pH 7.4 saturated with argon was added to the reaction mix  and the reaction mixture was kept for 2 hours at room temperature (RT). pHLIP-STINGa constructs were purified by reverse phase high-performance liquid chromatography (HPLC) using Zorbax SB-C18, 9.4×250 mm, 5 μm column (Agilent Technology) with a gradient from 10% to 75% acetonitrile in water containing 0.05% of trifluoroacetic acid (TFA). For preparation of fluorescent versions of the agents, Al647-pHLIP-STINGa and ICG-pHLIP-STINGa, N-acetylated versions of the pHLIP peptide AKDDQNPWRAYLDLLFPTDTLLLDLLWCG consisting of all L amino acids was used. First, pHLIP was conjugated with Pys-PAB-STING, followed by purification. Then, either ICG-NHS ester (Iris Biotech GmbH) or Alexa647-NHS ester (Life Technologies) was conjugated with the lysine residue at the N-terminal end of pHLIP in DMSO at molar ratio of 1:1.5. Sodium bicarbonate buffer (100 mM) at pH 8.3 was added to the reaction mix  and the reaction mixture was kept at RT until the conjugation was completed. The final purification was performed as described above. The products were lyophilized and characterized by matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass-spectrometry and analytical HPLC. The concentration of pHLIP-STINGa conjugates was determined by absorbance using the following molar extinction coefficients: for pHLIP-STINGa In vivogen) were analyzed for stability in plasma under the same conditions.To establish the stability of pHLIP(Laa)-STINGa and pHLIP(Daa)-STINGa in plasma, pHLIP-STINGa was mixed with single donor human or BALB/c mouse plasma (Innovative Research) at a concentration of 200 μM, and kept in plasma for 0, 2, 4 or 24 hours at 37°C. Plasma proteins were precipitated by methanol (1:5 volume ratio of plasma to methanol) and centrifugated for 10 min at 13.4 rpm. The supernatant was collected and analyzed by HPLC using a Zorbax SB-C18 4.6 × 250 mm, 5 μm column with a gradient from 10% to 75% acetonitrile in water containing 0.05% TFA. Chromatograms were recorded at 220 nm, 280 nm and 320 nm. As controls pHLIP(Laa), pHLIP(Daa), Pys-PAB-STINGa, SH-PAB-STINGa, where Pys-PAB-STINGa was conjugated with a Cys residue, and diABZI -STINGa was treated with dithiothreitol (DTT). At different time points (from 30 min to 2 hours of treatment) the samples were analyzed by HPLC using a Zorbax SB-C18 4.6 × 250 mm, 5 μm column with a gradient from 10% to 75% acetonitrile in water containing 0.05% TFA. The chromatograms were recorded at 220 nm, 280 nm and 320 nm. diABZI and pHLIP were used as controls at the same HPLC conditions.sn-glycero-3-phosphocholine (POPC) lipids (Avanti Polar Lipids) in chloroform were desolvated on a rotary evaporator and dried under vacuum for a minimum of 2 hours. The phospholipid film was rehydrated in 2 mM citrate phosphate buffer, pH 7.3, vortexed, and passed through the extruder (using a 50 nm membrane pore size) 21 times.The interactions of pHLIP(Laa)-STINGa with liposomes were investigated by recording the construct’s fluorescence and circular dichroism (CD) using a PC1 spectrofluorometer (ISS) and a MOS-450 spectrometer (Bio-Logic Science Instruments), respectively, with temperature control set to 25°C. Liposomes, constituting of large unilamellar vesicles were prepared by extrusion. 1-palmitoyl-2-oleoyl-Fluorescence spectra were recorded from 310 nm to 550 nm at an excitation wavelength of 295 nm and 1.0 mm sized slits. The excitation polarizer was set to 54.7 degrees (“magic angle”) while the emission polarizer was set to 0 degrees in order to reduce Wood’s anomalies. CD spectra were recorded from 190 to 260 nm with step size of 1 nm. The concentrations of pHLIP-STINGa and POPC were 7 μM and 1.4 mM, respectively. Also, the fluorescence of STINGa (diABZI) was recorded when excited at the 295 nm and 350 nm wavelengths.n) and the mid-point pK f transition. The fitting equations used wereThe pH-dependent insertion of pHLIP-STINGa into the lipid bilayer of POPC liposomes was studied by monitoring either the changes in fluorescence intensity at 400 nm or changes in the molar ellipticity at 230 nm as a function of pH. After the addition of aliquots of citric acid, the pHs of solutions containing pHLIP-STINGa and POPC liposomes were measured using an Orion PerHecT ROSS Combination pH Micro Electrode and an Orion Dual Star pH and ISE Benchtop Meter. The normalized fluorescence intensity or millidegree ellipticity values were plotted as a function of pH. The pH-dependence was fit with the Henderson-Hasselbach equation to determine the cooperativity  in combination with the MOS-450 spectrometer with temperature control set to 25°C. All samples were degassed before measurements to minimize air bubbles in the samples. pHLIP-STINGa and POPC samples were incubated overnight to reach equilibrium, when most of the agent was associated with liposome lipid bilayers. To follow pHLIP-STINGa insertion into a membrane, a solution containing 14 μM pHLIP-STINGa and 2.8 mM POPC was mixed with citric acid to lower the pH from pH 8 to 3.5. To monitor fluorescence intensity changes during pHLIP-STINGa insertion into POPC liposomes induced by the pH drop, the emission signal was observed through a cut-off 320 nm filter at an excitation of 295 nm.For oriented circular dichroism (OCD) measurements, supported bilayers were prepared on quartz slides with special polish for far UV measurements (Starna). The procedure of slide cleaning included the following steps: 1) soaking in cuvette cleaner solution for 24 hours, 2) rinsing with de-ionized distilled water, 3) sonicating for 10 min in 2-propanol, 4) sonicating in acetone, 5) sonicating in 2-propanol once again, 6) rinsing with de-ionized water, 7) soaking in a piranha solution consisting of 25% hydrogen peroxide and 75% sulfuric acid, and 8) rinsing with Milli-Q purified water. A POPC lipid monolayer was deposited on a quartz substrate by the Langmuir-Blodgett (LB) method using (KSV minitrough). For the LB deposition, a small amount of POPC lipid in chloroform was spread on the surface of the subphase and solvent was allowed to evaporate for about 10 min. Next, the monolayer was compressed to 32 mN/m. When the surface pressure was stabilized the first slide was inserted into the trough and held there for 60 seconds so the surface pressure would stabilized again, then it was pulled out from the subphase with speed of 10 mm/min. The second layer was created by fusion with POPC vesicles. About 80 μl of either samples containing 7 μM pHLIP-STINGa and 0.7 mM POPC in 2 mM pH 5.0 or in 2 mM pH 3.3 citrate phosphate buffers or POPC blank containing 0.7 mM POPC (no pHLIP-STINGa) in citrate phosphate buffer was spread onto the slide. The process was repeated for eight more slides, then they were stacked on top of each other. The spacers between the slides kept them from sticking to each other. The “0-hour” OCD spectra were measured for samples at both pHs and POPC blank. Then, slides were kept at 100% humidity at 4°C for 6 hours. After 6 hours, excess solution was shaken off each slide and replaced with 80 μL of buffer of corresponding pH. The slides were again stacked together while filling with the buffer to have a complete set of 8 slides (16 bilayers) and stored at 100% humidity at 4°C for another 6 hours. At the end of the 12-hour incubation period, the “12-hour” OCD spectra were measured. The POPC blank OCD spectrum was subtracted from the OCD spectra of samples.All data were fit to the appropriate equations by nonlinear least squares curve fitting procedures employing the Levenberg Marquardt algorithm using Origin 8.5.2 and 95% air at 37°C. Cells were seeded in 96-well plates at a density of 75,000 cells/well. To generate M2 polarized macrophages, cells were treated first with 185 ng/mL phorbol 12-myristate 13-acetate (PMA) for 6 hours and then 20 ng/mL of interleukin 4 (IL-4) IL-4 and 20 ng/mL of interleukin 13 (IL-13) (both from PeproTech) were added for another 16 hours of treatment. At the completion of polarization, the growth medium was replaced with Dulbecco’s Modified Eagle Medium (DMEM) medium without FBS, pH 6.9, containing increasing amounts of pHLIP(Laa)-STINGa or STINGa (up to 10.0 µM). After a two-hour incubation, an equal volume of RPMI supplemented with 20% heat-inactivated FBS was added, and cells were incubated for another 48 hours. SEAP activity was accessed using the QUANTI-Blue™ Solution (Invivogen) to evaluate type I interferon protein levels: 150 μl of the colorimetric reagent was added to 50 μl of cell supernatant for 30 min, 37°C, followed by absorption measurement at 655 nm.THP-1-Blue™-ISG cells (Invivogen) expressing an interferon (IFN) regulatory factor (IRF)-inducible secreted embryonic alkaline phosphatase (SEAP) reporter construct were used. Cells were maintained in RPMI growth medium supplemented with L-glutamine, sodium pyruvate, 10% fetal bovine serum (FBS), normocin and ciprofloxacin hydrochloride in a humidified atmosphere of 5% CO2 and 95% air at 37°C. Cells were seeded in 96-well plates at a density of 30,000 cells/well. To generate M2 polarized macrophages, cells were treated first with 185 ng/mL PMA for 6 hours alone and then 20 ng/mL of IL-4 and IL-13 were added for another 16 hours of treatment. At the completion of polarization, the medium was replaced with DMEM without FBS, pH 6.4, containing increasing amounts of pHLIP(Laa)-STINGa. After a three-hour incubation, an equal volume of RPMI supplemented with 20% FBS was added. Cell viability was assessed after 48 hours using the CellTiter 96 AQueous One Solution Cell Proliferation Assay (Promega); the colorimetric reagent was added to cells for one hour, followed by absorption measurement at 490 nm.THP1 cells  were maintained in RPMI growth medium supplemented with 2-mercaptoethanol, 10% FBS and ciprofloxacin hydrochloride in a humidified atmosphere of 5% COAll animal studies (unless it stated differently) were conducted at the University of Rhode Island (URI) according to the approved by URI Institution Animal Care and Use Committee (IACUC) animal protocol AN04-12-011. The studies complied with the principles and procedures outlined by the National Institutes of Health for the care and use of animals.4 CT26 murine colorectal cancer cells  were injected subcutaneously (SQ) in 100 μl of growth medium into the right flank of female Balb/c mice or athymic female nude mice (strain Hsd Athymic Nude-Foxn1nu) ranging in age from 7 to 9 weeks . On day 1, when tumors reached size of 100 mm3  or 400-700 mm3 (“large tumors”), mice were randomized into groups, body weight was measured and agents including pHLIP(Laa)-STINGa, pHLIP(Daa)-STINGa, pHLIP(Laa), STINGa (diABZI) or vehicle were given as a single intraperitoneal (IP) or intravenous (IV) injection. Vehicle, pHLIP(Laa), STINGa (diABZI) and pHLIP(Laa)-STINGa were given as a single IP injection of 100 μM 300 µl. pHLIP(Daa)-STINGa was given as a single IV injection of 200 μM 150 μl. The compounds were dissolved in DMSO as a stock solution and transferred to 20% PEG400 in saline containing 0.9% sodium chloride (vehicle). The residual DMSO in the final solution injected into animals was less than 2%. Tumor volume and body weight were measured 3 times per week throughout the study. Measurements of tumors were performed using calipers, and the tumor volume (V) was calculated with the formula:For the treatment of CT26 tumors, 5x10L is the length and W is the width of the measured tumor. Mice were removed from the study and euthanized when the tumor volume was greater than 2000 mm3.where 5 4T1 murine breast cancer cells  into their right flanks. Also, a control group of female Balb/c mice received 105 4T1 cancer cells into the right flank and tumor growth was compared between groups.Mice in the pHLIP-STINGa treated group, which stayed tumor-free, were re-challenged with tumor cells injected into the opposite flank on day 61 after a single injection of pHLIP-STINGa. Tumor-free mice were kept for additional 40 days  and most of them were euthanized. Five tumor-free mice on day 101 received another SQ injection of 105 4T1 murine breast cancer cells  were injected SQ in 100 μl of growth medium into the right flank of Balb/c female mice ranging in age from 7 to 9 weeks (Envigo). On day 1, when tumors reached 100 mm3 in volume, the body weight was measured, and mice were randomized into four groups. On day 1 mice from groups #2 and #4 received a single IP injection of pHLIP(Laa)-STINGa (100 μM 300 μl). On days 4, 9, 14 mice from groups #3 and #4 received three IP injections of anti-mouse PD-1 antibody , 250 μg/mouse per injection. Mice from the control group (group #1) did not receive any treatment. Tumor volumes and body weight were measured 3 times per week, and mice were euthanized when the tumor volume was greater than 1500 mm3.For the treatment of 4T1 triple negative breast tumors, 104 CT26 cancer cells were injected SQ in 100 µl of growth medium into the right flank of female Balb/c mice. When tumors reached 150-250 mm3 in volume, the mice received a single IV or IP injection pHLIP(Laa)-STINGa or pHLIP(Daa)-STINGa, STINGa or no injections. Animals were euthanized at 4-, 16- and 24-hours post-injection, blood and tumors were collected. Blood samples were kept for 40 min at RT, centrifuged at 5000 g for 20 min at +4°C and supernatant (serum) was collected. Tumors were frozen in liquid nitrogen. Both, the serum and tumor tissue samples were kept at -80°C until further processing and analysis. The tumor samples were processed while on ice, using a bullet blender (Next Advance) with 1 mm diameter zirconium silicate beads (Next Advance). The supernatant of the processed tumors was used for enzyme-linked immunoassay (ELISA) assays. Matched antibody pair kits for mouse tissue necrosis factor alpha (TNF-α) , mouse interleukin 6 (IL-6) (Abcam), and a pre-coated plate for mouse IFN-β (PBL Assay Science) were used. ELISA assays were performed using the serum and tumor samples. For TNF-α the capture antibody was diluted in phosphate buffer saline (PBS) (Sigma-Aldrich), and for IL-6 the capture antibody was diluted in coating buffer (Abcam). The diluted capture antibodies were incubated in the plates overnight at +4˚C and washed the next day with PBS/Tween washing buffer (Sigma-Aldrich). The TNF-α plate was blocked using 2% bovine serum albumin (BSA) (Thermo Scientific) in washing buffer, while the IL-6 and IFN-β plates are blocked using dilution buffers from the corresponding kit. Blocking was done for 2 hours at RT on an orbital shaker at 200 rpm. After blocking, the plates were washed and then incubated with the diluted tumor and serum samples along with the corresponding standard solutions for each ELISA kit. The samples were incubated for 2 hours at RT on an orbital shaker at 200 rpm. The TNF-α and IFN-β plates were incubated for 1 hour at RT with a diluted detection antibody conjugated with horseradish peroxidase (HRP). The IL-6 plate was incubated for 1 hour at RT with a diluted detection antibody conjugated with biotin followed by incubation for 1 hour at RT with the diluted HRP-streptavidin conjugate (Abcam). All plates were washed and incubated with 3,3’,5,5’-tetramethylbenzidine (TMB) (Invitrogen) and peroxide solution mixed at a ratio of 1:1 (Thermo Scientific) for up to 20 min, then stop solution (10% H2SO4) was added to the plates. The signal from the wells was quantified by absorbance measured at 450 nm using a Bio-Rad iMark microplate reader. Different dilution schemes were tested in duplicate and antibody standards were used to plot calibration curves.To establish levels of cytokines in blood and tumor samples, 5x104 of CT26 cancer cells were injected SQ in 100 µl of growth medium into the right flank of female Balb/c mice and tumors were grown until they reached 150-200 mm3 in volume. For PK and biodistribution studies, a single tail vein injection of 200 μM 100 μl of ICG-pHLIP(Laa)-STINGa was performed. Animals were euthanized at 2, 4, 24, 48, 72 and 96 hours post-injection, blood was collected in K2 EDTA vacutainer blood collection tubes (BD), and necropsy was performed immediately after euthanization. Blood, tumors and major organs  were collected, and imaged ex vivo immediately after necropsy. Blood (150 µl) was imaged in 96-well plate with black bottom and walls. The zero-time point (0 min) was obtained by imaging of ICG-pHLIP-STINGa diluted in blood collected from a control mouse that did not receive any injection (the dilution was made based on the assumption that a mouse contains 80 ml/kg of blood). The fluorescence at zero-time point was taken as 100% and fluorescence recorded at 2, 4, 24 and 48 hrs p.i. were calculated as a percentage of zero-time point signal. The points were fitted using single exponential decay function to establish half-life time.For pharmacokinetics (PK), biodistribution, pH imaging studies and immunohistochemistry, 5x10in vivo imaging, Balb/c and athymic nude mice were given single IP (200 μM 100 μl) or IP (300 μM 150 μl) injections of ICG-pHLIP(Laa)-STINGa when tumors reached 150-250 mm3, and in vivo imaging was performed at 1, 2, 4, 24, 40-48, 74, 100, 170 and 195 hrs p.i.For For pH imaging studies mice were separated into 2 groups. On day 1, mice from group #1 received a single IP injection of pHLIP(Laa)-STINGa (100 μM 300 µl), while mice from the control group #2 did not receive any treatment. On day 3, mice from groups #1 and 2 received a single IP injection of 50 μM 100 µl of the acidity imaging probe ICG-pHLIP . On day 4 (or 24 hours after ICG-pHLIP injection) all animals were euthanized, tumors were collected, cut in half and imaged.in vivo and ex vivo bright field and near-infrared fluorescent imaging was performed using a Stryker 1588 AIM endoscopic system with L10 AIM Light Source (808 nm excitation and collection of light in the range of approximately of 815 to 850 nm), and a 1588 AIM Camera using a 10 mm scope. The lens was kept at a fixed distance from the surface of the organs, within an enclosed (light-protected) area. The imaging was performed at three different settings. The digital images of organs were saved in the green channel, transferred into 8-bit files and processed using ImageJ program. A threshold was set from pixel intensity in the range from 1 to 255, leaving out the background with pixel intensity 0. Brightfield images were used to establish the borders of the organs and tumors. The calculated total fluorescence intensity and total area of each organ were used to calculate the mean organ fluorescence.The 5 CT26 cancer cells were injected SQ in 100 µl of 0% matrigel into the flank of female Balb/c mice (age 8 to 12 weeks). When tumors reached 150-250 mm3 in volume mice were separated into two groups. Eight mice from the treated group #1 received a single IP injection of Al647-pHLIP(Laa)-STINGa (300 µM 100 µl), and five mice from the control group #2 received single IP injection of vehicle (1% DMSO in PBS). 24 hours later all animals were euthanized, and tumors were collected for processing. Tumor stroma and immune cells were identified using the following markers:Animal studies on mice were conducted at the Charles River Discovery Service in compliance with the principles and procedures outlined by the National Institutes of Health for the care and use of animals. Uptake of Al647-pHLIP(Laa)-STINGa by tumor cells within CT26 tumors was analyzed by fluorescence activated cell sorting (FACS) analysis. 3x10+, CD3+, CD11b-, CD4+, CD8-CD4 T cells: CD45+, CD3+, CD11b-, CD4-, CD8+CD8 T cells: CD45+, CD3+, CD11b-, CD4+, CD25+, FoxP3+Treg: CD45+, CD3-, CD11b+, F4/80-, Ly6Chigh, Ly6G-mMDSC: CD45+, CD3-, CD11b+, F4/80-, Ly6Clow, Ly6G+gMDSC: CD45+, CD11b+, F4/80+, CD206-M1: CD45+, CD11b+, F4/80+, CD206+M2: CD45+, CD11b+, CD11c+, MHCII+, F4/80-DC: CD45-, CD45-, CD140b+CAF: CD3The staining was performed for tumor samples, Fluorescence Minus One (FMO) controls and Single Color Controls (SCC) as indicated below:Tumor: Live/Dead, CD45, CD3, CD4, CD8, CD25, FoxP3, CD11b, F4/80, Ly6C, Ly6G, CD206, CD11c, MHCII, CD140bTumor-FMO: CD3, CD25, FoxP3, F4/80, Ly6C, Ly6G, CD206, CD11c, MHCII, CD140bSCC: Unstained, CD45, CD3, CD4, CD8, CD25, FoxP3, CD11b, F4/80, Ly6C, Ly6G, CD206, CD11c, MHCII, CD140b, Live/Dead7 cells/mL and placed into individual wells of a 96-well plate and kept on ice. All incubation steps were carried out protected from light. The washing was performed by spinning the plate at 300x g (or 400x g) for 3 minutes and discarding the supernatant. Live/Dead reagent was added to each sample and incubated at 4°C for 15 minutes followed by washing. Fc-block  diluted in Staining Buffer (BD) was added to the samples and incubated for 10 min at 4°C followed by addition of cell surface antibodies diluted in Staining Buffer supplemented with Brilliant Stain Buffer Plus (BD) for 30 min at 4°C and consequent washing. Cells were fixed in FoxP3 Fix/Perm solution and incubated for 30 min at room temperature followed washing. For single color controls, one drop of Ultra Comp Beads (Thermo Fisher) was added to each single-color control well. For Live/Dead controls one drop of ArC Amine Reactive Compensation Bead (Life Technologies) were added followed by addition of each antibody to appropriate well. Isotype control-Al647 clone MOPC-21 (BioLegend) was used for Alexa47 channel, where Al647-pHLIP-STINGa was imaged. The incubation steps were followed by washing steps. The number of cells in the control and treated groups and the cellular uptake of Al647-pHLIP-STINGa was established.The following anti-mouse antibodies were used: CD45-APC-Fire750 clone 30-F11, CD8a-BV650 clone 53-6.7, CD25-BV605 clone PC61, F4/80-PE-Dazzle-594 clone BM8, Ly-6C-FITC clone HK1.4, Ly-6G-BV785 clone 1A8, CD206-BV421 clone C068C2, CD140b-PE clone APB5, CD11c-BV711 clone N418, I-A/I-E-PE/Cy7 clone M5/114.15.2 from BioLegend; CD3e-BUV496 clone 145-2C11, CD4-BUV395 clone GK1.5; CD11b-BUV737 clone M1/70 from BD Biosciences, FoxP3 PerCP-Cy5.5 clone FJK-16s from Thermo Fisher and Live/Dead Aqua-V500 from Life Technologies. The procedure for tumor processing was the following: tumor samples were dissociated according to the manufacturer’s instructions using the gentleMACS™ protocol “Tumor Dissociation Kit”. Samples were filtered through a 70 µm cell strainer and rinsed twice in PBS/2.5% FBS buffer and total sample volumes were measured. Single cell suspensions were prepared in PBS pH 7.4 at 1x103 in volume, mice received a single IP injection of Al647-pHLIP(Laa)-STINGa (300 µM 100 µl). Tumors were cryo-sectioned using a ThermoFisher HM525 NX to make 10-20 µm sections. Sections were stained with fluorescent antibodies, CD206-AL594 (BioLegend), CD68-AL594 (BioLegend), CD140b-AL488 (Invitrogen) and 4′,6-diamidino-2-phenylindole (DAPI) (Sigma-Aldrich) or hematoxylin and eosin (H&E) using hematoxylin 7211 (ThermoFisher) and eosin Y (Poly Scientific). Sections were dried in air for 10 min, then washed with distilled water for 2 min followed by fixation in 4% paraformaldehyde 37% (Sigma-Aldrich) for 12 min, washing with Dulbecco′s phosphate buffered saline (DPBS) (Sigma-Aldrich) for 5 min and drying in air for 10 min. A cover slide was placed on a layer of petroleum jelly (Equate), which was applied to the slide around the tissue. Sections were incubated with blocking buffer containing 5% of 10% BSA (ThermoFisher) for 2 hours at RT followed by washing. Sections were treated with antibody in blocking buffer for 2 hours at RT, followed by washing. A coverslip is mounted on top of the tissue using organo/limonene mount. Imaging of the tissue sections were performed on an EVOS Fl Auto 2 fluorescence inverted microscope using 10x, 20x and 40x objectives in brightfield and fluorescent modes with appropriate filters.When the tumors reached 150-250 mmp-levels. Log rank , Breslow method  and Tarone-Ware method  were used to establish p-levels for survival plots.The Kolmogorov-Smirnov two-tailed nonparametric test was used to establish via a self-immolating disulfide cleavable linker to the membrane-inserting end of pHLIP peptides consisting either of all L or all D amino acids (Laa and Daa)  Table S1pHLIP is expected to translocate STINGa across the membrane into the cytoplasm, where the S-S bond will be reduced, followed by linker self-immolation and release of the original, unmodified STINGa as a dimeric diABZI. In a model experiment we induced cleavage of the S-S bond by dithiothreitol (DTT) and observed that 88% of immolation was completed within 1 hour, releasing STINGa in its unmodified form -inducible secreted embryonic alkaline phosphatase (SEAP) reporter construct. We found that THP1-Blue cells exhibited a concentration-dependent activation of IRF signaling when polarized by phorbol 12-myristate 13-acetate (PMA), interleukin 4 (IL-4) and interleukin 13 (IL-13) into M2-type macrophages and treated with pHLIP-STINGa. As shown below, M2-type macrophages are the most abundant immune cells within the CT26 tumors we investigated. Thus, we confirmed successful intracellular delivery and release of STINGa by pHLIP (3. The murine CT26 colon tumor cell line is a well-established model for testing immuno-oncology therapeutics and it exhibits a weak response to ICIs. Fluorescence imaging in vivo shows tumor targeting (For pharmacokinetics (PK), biodistribution, tumor uptake and immuno-histochemistry studies, fluorescent dyes, either near infrared indocyanine green (ICG) or Alexa647 (Al647), were conjugated to the non-inserting end of the pHLIP to make ICG-pHLIP-STINGa or Al647-pHLIP-STINGa fluorescent agents. ICG-pHLIP-STINGa was given as a single intravenous (IV) injection when CT26 tumors established in the right flanks of female Balb/c mice reached volumes of about 150-300 mmargeting . Thus, pCytokine levels induced in tumors and serum were measured following a single IV injection (200 µM 150 μl) of STINGa or pHLIP-STINGa (+) cells and 15% of all live cells. We performed a fluorescence activated cell sorting (FACS) analysis of the cells from CT26 tumors in mice 24 hrs after a single intraperitoneal (IP) injection of Al647-pHLIP-STINGa (300 µM 100 μl). We established that 74% of all CAFs  and 71% of CD206+ TAMs  were targeted by Al647-pHLIP-STINGa  and DCs  were targeted by the agent, and about 20% of CD8 T-cells  and gMDSCs  were targeted by Al647-pHLIP-STINGa. DCs constitute 2% of all immune (CD45+) cells and 0.7% of all live cells; gMSDCs constitute 13% of all immune (CD45+) cells and 5% of all live cells, and CD8 T-cells constitute 12% of all immune (CD45+) cells and 4% of all live cells within CT26 tumors. Targeting of the most abundant non-cancer cells within TME, CAFs and CD206+ macrophages, was confirmed by immunohistochemistry performed on CT26 tumors collected 24 hrs after Al647-pHLIP-STINGa administration  or IV (200 µM 150 μl) injection was administered to mice assigned in four groups: vehicle (20% PEG400/0.9% NaCl); pHLIP; STINGa; or pHLIP-STINGa, where pHLIP(Laa)-STINGa was used in the IP injection group and pHLIP(Daa)-STINGa was used in the IV injection group. Tumor growth was monitored for 60 days or until the tumor volume endpoint was achieved   to 20% in large tumors (~500 mm3), and the population of CD3+ cells drops from 28% to 7%. Larger tumors contain more CD11b+ myeloid cells. The proportion of immune cells and their composition typically affects treatment efficacy. To study the treatment of larger tumors, a single IP injection of pHLIP-STINGa (100 µM 300 μl) was given when CT26 tumors in Balb/c mice reached a volume of 400-700 mm3. Three out of 10 mice developed larger tumors by 60 days, while the other mice slowly fought the cancer and became tumor-free  that had remained tumor-free for 60 days were inoculated with CT26 cells in their previously uninoculated left flanks and were monitored for an additional 40 days. One mouse from IP small tumor group, 2 mice from IV small tumor group and 2 mice from IP large tumor group developed tumors. Thus, 20 out of the 25 mice (80%) remained tumor-free, indicating the development of immune memory and the consequent rejection of the CT26 cancer cells  or 3 IP injections on days 4, 9 and 14 of an anti-PD-1 antibody (250 µg/injection) or a combination of pHLIP-STINGa with the PD-1 antibody series. While each treatment delayed the growth of 4T1 tumors slightly (p< 0.02), the longest survival was observed for the combination treatment of a single pHLIP-STINGa followed by multiple PD-1 antibody injections (p< 0.004)  when tumors reached a volume of ~100 mmIn all treatment groups, the single injection of pHLIP-STINGa (IP or IV) led to transient distress and slight transient weight loss (≤10%), with complete recovery within 3-4 days  was given to mice in the “treated” group. On day 3, a single IP injection of the acidity probe, ICG-pHLIP (50 µM 100 μl), was given to the “treated” and “control (untreated)” groups of mice, and 24 hrs later (on day 4), mice were euthanized, tumors were collected, cut in half and imaged  overexpressed on tumor cell surfaces), contributing to the acidification of the extracellular space  or in hypoxic conditions (Pasteur effect) , 20. Lacar space . Thus, ear space , 26.pHLIP peptides have been shown to sense cell surface pH and target acidic tumors. At the low cell surface pH of a metabolically overactive cell, several carboxyl groups within a pHLIP become protonated, triggering peptide folding and insertion across the cell membrane to form a stable transmembrane helix. The dielectric environment at the membrane surface shifts the pKa’s of the carboxyl groups toward higher pHs, and a moderately low local pH promotes their protonation. A variety of imaging and therapeutic agents have been successfully delivered to tumors by pHLIP peptides , 27–34. via a S-S cleavable self-immolating linker and found it to have desirable properties. The pK of insertion into a model membrane is 6.1-6.4, which is in the range of pH at the surface of metabolically active cells in diseased tissues. We also found a fast (msec) rate of insertion, well suited for cell targeting in vivo. Characterization of the pHLIP-STINGa agent revealed significant binding to plasma proteins. The highest stability and strongest plasma protein affinity was found for pHLIP(Daa)-STINGa (wherein the pHLIP is made from D-amino acids). The half-life of fluorescent pHLIP(Laa)-STINGa in a mouse was established to be about 6 times higher compared to STINGa alone, a significantly improved PK. Slow blood clearance of other pHLIP imaging and therapeutic agents in animals has previously been observed (We used STINGa (diABZI), conjugated to the membrane-inserting end of a pHLIP peptide observed , 39, 40 3) triggers complete tumor eradication (90% incidence rate) and the mice remained tumor-free for 60 days after pHLIP-STINGa administration. All mice receiving the same dose of untargeted STINGa developed tumors within 20-35 days. Only 13% of tumor cells remained viable 16-24 h after pHLIP-STINGa administration. A significant increase in the level of TNF-α was observed within the TME. TNF-α triggers the disruption of tumor vasculature, reduces intra-tumoral interstitial fluid pressure (IFP) and promotes the flow of blood to tumors, and TNF-α is used to improve drug delivery to tumors  remained tumor free for another 40 days . Thus, a single pHLIP-STINGa injection promoted the development of T-cell immune memory. The importance of T-cells was confirmed in a study performed on athymic nude mice lacking T-cells. pHLIP-STINGa did not exhibit any statistically significant therapeutic efficacy on CT26 tumors in nude mice, while intratumoral hemorrhage was observed as well. We expect that the tumor stroma was destroyed, but the lack of T-cells did not allow tumor eradication.3) tumors we treated mice with large (~500 mm3) CT26 tumors. A single IP injection of pHLIP-STINGa into mice with large tumors (400-700 mm3) led to tumor eradication in 7 out of 10 treated animals, and the complete treatment response took 20-40 days. Large tumors have many cancer cells to target [80% of all tumor cells are cancer cells vs 35% of cancer cells in small CT26 tumors (+ cells). Successful treatment of large CT26 tumors holds promise for the eradication of immunosuppressive tumors with a high number of myeloid cells.In addition to the treatment of small . Also, like CT26 tumors, 4T1 tumors are acidic and very well targeted by pHLIP , or antibodies labeled with radioactive isotopes, or radiation therapy, which could be significantly enhanced under non-hypoxic conditions. Combinations with pHLIP-STINGa might decrease the effective doses of these therapeutics. Different types of tumor development and potential treatment options are presented in the following scheme  of metabolically active cells within the tumor microenvironment. Since the tumor microenvironment is complex, such an approach in targeting and delivery leads to a significant synergistic effect. A single injection of pHLIP with immuno-activator (STINGa) induces production of cytokines, obliterates tumor stroma and increases the tumor pH, which results in the eradication of tumors and the development of immune memory.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The animal study was reviewed and approved by The University of Rhode Island Institution Animal Care and Use Committee, Animal protocol AN04-12-011.AM, DE, OA and YR designed research; AM, MD, HV, OA and YR performed the experiments and analyzed data; DE, OA, and YR wrote the paper. All authors read, provided feedback on, and approved the manuscript for publication. MD and HV equally contributed to the work.This work was supported by NIH grant R01 GM073857 .The authors are grateful for the support of Dr. Sonia Sequeira for discussions, as well as members of the URI Institutional Development Award (IDeA) Network for Biomedical Research Excellence supported by NIH P20 GM103430, and Stryker Endoscopy  for providing their imaging system.DE, OA, and YR are founders of pHLIP, Inc., and they have shares in the company. pHLIP, Inc provided funding for synthesis and purification of modified STINGa and ICG-pHLIP, and the FACS analysis performed at the Charles River Discovery Labs.The IP for pHLIP-STINGa was exclusively licensed to pHLIP, Inc.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.The handling editor PM declared a shared affiliation with the author DE at the time of review.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Alternative splicing (AS) of RNA is a fundamental biological process that shapes protein diversity. Many non-characteristic AS events are involved in the onset and development of acute myeloid leukemia (AML). Abnormal alterations in splicing factors (SFs), which regulate the onset of AS events, affect the process of splicing regulation. Hence, it is important to explore the relationship between SFs and the clinical features and biological processes of patients with AML.This study focused on SFs of the classical heterogeneous nuclear ribonucleoprotein (hnRNP) family and arginine and serine/arginine-rich (SR) splicing factor family. We explored the relationship between the regulation patterns associated with the expression of SFs and clinicopathological factors and biological behaviors of AML based on a multi-omics approach. The biological functions of SRSF10 in AML were further analyzed using clinical samples and in vitro experiments.Most SFs were upregulated in AML samples and were associated with poor prognosis. The four splicing regulation patterns were characterized by differences in immune function, tumor mutation, signaling pathway activity, prognosis, and predicted response to chemotherapy and immunotherapy. A risk score model was constructed and validated as an independent prognostic factor for AML. Overall survival was significantly shorter in the high-risk score group. In addition, we confirmed that SRSF10 expression was significantly up-regulated in clinical samples of AML, and knockdown of SRSF10 inhibited the proliferation of AML cells and promoted apoptosis and G1 phase arrest during the cell cycle.The analysis of splicing regulation patterns can help us better understand the differences in the tumor microenvironment of patients with AML and guide clinical decision-making and prognosis prediction. SRSF10 can be a potential therapeutic target and biomarker for AML.The online version contains supplementary material available at 10.1186/s12967-022-03868-9. Acute myeloid leukemia (AML) is a hematological malignancy derived from hematopoietic stem cells, and its pathogenesis is still unclear . PatientNOTCH2 and FLT3 genes encode functional proteins that exert pro-oncogenic effects and generate resistance against targeted inhibitors by affecting key downstream signaling targets  [Aberrant splicing of genes promotes AML progression as well as treatment resistance, including the formation of various specific splice variants and the onset of non-characteristic alternative splicing (AS) events , 7. Thesand ERK) . Among aand ERK) . In AML,and ERK) , 11.AS is a complex biological process that can involve coordinated interactions between more than 200 molecules to support or inhibit splicing regulation at specific target sites of precursor messenger RNA (pre-mRNA) . In thisSRSF10, a gene that plays an active tumor-promoting role in many cancers but whose expression has not been reported in AML. We observed that the expression levels of SRSF10 were significantly upregulated in AML samples compared to those in normal blood tissues. Furthermore, we elucidated the mechanism of SRSF10 in AML via further experiments.This study aimed to conduct an in-depth analysis of the relationship between SFs of the hnRNP and SR families and the biological features of AML and to enhance the understanding of the mechanism by which these SFs regulate aberrant AS events in AML. These analyses may help us to better understand the role of AS pathogenesis on the development of AML. We applied bioinformatics analysis methods to transcriptome sequencing data combined with clinical information to explore the relationship among SFs, the prognosis of patients with AML, and tumor microenvironment. The results of these differential features and prognostic analysis will also provide reference values for the study of molecular mechanisms of AML, clinical prognosis prediction, and the design of personalized treatment regimens. Finally, we focused on the splicing factor https://xenabrowser.net/datapages/) for 173 patient samples in the Cancer Genome Atlas-Acute Myeloid Leukemia (TCGA-LAML) and 337 healthy whole blood control samples in the Genome Tissue Expression (GTEx). The alternative splicing data in TCGA-LAML were downloaded in the TCGA SpliceSeq database, including the splicing percentage values (PSI) of alternative splicing events in each sample. PSI values ranging from 0 to 100% represented the occurrence of each AS event. Seven types of AS events were recorded, which are listed as follows: exon skipping (ES), mutually exclusive exon (ME), retained intron (RI), alternative promoter (AP), alternative terminator (AT), alternative donor site (AD), and alternative acceptor site (AA). Finally, we downloaded somatic mutation and copy number variation data from the TCGA database for patients with AML. RNA-seq data were normalized to transcripts per million (TPM) values and log2 transformed. Somatic mutation data and copy number variation data were downloaded from the TCGA database . The microarray data and prognostic information of the validation cohorts for the risk score model  were downloaded from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/). SFs from 20 HNRNP families and 12 SR families were analyzed in this study, which are listed as follows: SRSF1, SRSF2, SRSF3, SRSF4, SRSF5, SRSF6, SRSF7, SRSF8, SRSF9, SRSF10, SRSF11, SRSF12, HNRNPA0, HNRNPA1, HNRNPA2B1, HNRNPA3, HNRNPAB, HNRNPC, HNRNPCL1, HNRNPD, HNRNPDL, HNRNPF, HNRNPH1, HNRNPH2, HNRNPH3, HNRNPK, HNRNPL, HNRNPM, HNRNPR, HNRNPU, HNRNPUL1, and HNRNPUL2. All data were analyzed using the R language software R 4.02 and corresponding software packages.We downloaded transcriptome sequencing data and clinical information from the XENA database  method was used to verify the reliability of the splicing regulation patterns identified based on SFs.https://www.gsea-msigdb.org/gsea/msigdb/), and the adjusted P-value < 0.05 was used to identify the differences of enrichment scores among different groups. To explore the signaling pathways associated with differentially expressed genes (DEGs), we performed the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The biological functions of these genes were annotated via Gene Ontology (GO). These functions were analyzed in the“clusterProfiler” package. Gene sets for different types of immune-function related features, such as antigen-presenting cell co-stimulation/co-inhibition and T cell co-stimulation/co-inhibition, were collected from previous studies and then analyzed for enrichment scores using the GSVA algorithm [In order to explore the differences in biological processes among different splicing regulatory patterns, we used the “GSVA” package to conduct GSVA enrichment analysis. In non-parametric and unsupervised analysis methods, GSVA is typically performed to calculate enrichment scores to estimate the activity levels of pathways and biological processes corresponding to gene sets in samples. We downloaded the “h.all.v7.4.symbols” gene set from MSigDB database  algorithm was used to predict the response of different splicing regulatory patterns to anti-PD-1 and anti-CTLA4 immune checkpoint inhibitors.The software package “pRRophetic” was used to predict the half-maximal inhibitory concentration (IC50) of drugs commonly used to treat AML in each sample. IC50 indicates the effectiveness of a substance in inhibiting a specific biological or biochemical function, and a smaller value indicates a better effect. The SubMap  of the model. The following formula was used to calculate the risk score for each sample:In order to more accurately predict the OS of patients, we combined clinical features significantly associated with the prognosis of AML patients with the risk scoring model and developed a nomogram with three signatures: age, cytogenetic risk, and prognostic risk score model. Simultaneously, the ROC curve and calibration curve were drawn to evaluate the predictive performance of the nomogram.2. A lentivirus containing SRSF10 siRNA was purchased from Hanhsinhsinh  to infect THP1 cells and select cells for puromycin resistance. Real-time polymerase chain reaction (RT-PCR) was performed using a Japanese TAKARA kit using the ABI7500 instrument. Western blot experiments were performed with rabbit anti-β-tubulin  and anti-SRSF10  antibodies purchased from Cell Signaling Technology .Two batches of AML samples were collected with the approval of the Medical Ethics Committee of the Second Affiliated Hospital of Nanchang University, and the participants were informed at the same time. The first batch comprised bone marrow samples from four patients with AML and peripheral blood samples from eight healthy individuals. The second batch comprised peripheral blood samples from 22 patients with AML and 23 healthy individuals, and mononuclear cells were isolated. The mononuclear cells we obtained were left over from the necessary medical tests of the participants and would not affect their benefits. AML cell line THP1 was cultured in the RPMI1640 medium containing 10% fetal bovine serum and 1% penicillin–streptomycin in an incubator at 37 °C in a humidified atmosphere with 5% CO4 cells of different treatment groups were seeded in a 96-well plate, and each group was repeated three times. A total of 10 µL of CCK8 was added at 0, 24, 48, and 72 h, respectively. After incubation at 37 °C for 2.5 h, the OD was detected at 450 nm using a microplate reader. For EdU staining, 1 × 106 cells were incubated with EdU solution diluted at a ratio of 1:1000 at 37 °C for 2.5 h, fixed with paraformaldehyde at room temperature, and decolorized with 2 mg/ml of glycine. After subsequent washing during Apollo staining and Hoechst33342 chamber staining, fluorescence microscopy was performed. For apoptosis assays, cells were stained using the annexin V-PE/7-AAD Apoptosis Assay Kit and subsequently analyzed via a flow cytometer. For the cell cycle, the cells were fixed with 75% ethanol precooled at 4 °C for 3–4 h and centrifuged at 1000 R for 5 min in a low-speed centrifuge. The supernatant was discarded and washed once with PBS. Subsequently, FITC dye was added, followed by incubation in a dark environment for about 15 min, and the cells were tested using a flow cytometer.Cell proliferation was detected by Cell Counting KIT-8 (CCK-8) and EdU staining. For CCK8, 2 × 10We used the Wilcoxon rank sum test or the Kruskal–Wallis test to determine differences between groups. A two-sided P value of < 0.05 was considered statistically significant.We first analyzed the expression characteristics of two splicing family regulators in AML samples. The expression of 31 out of the 32 SFs was detected in both AML and normal samples. Compared with normal samples, the expression of 10 SFs  was significantly down-regulated in AML samples. The expression of 17 SFs  was up-regulated in AML samples. The expression of SRSF3, HNRNPA2B1, HNRNPA3, and HNRNPA0 did not demonstrate significant differences  > 1 and a high expression of these genes predicted poor prognosis of patients. However, the 20 SFs of hnRNP family comprised 12 risk factors and 8 protective factors (HR < 1) , respectively, of which 53 contains both in two groups of DEGs  significantly related to the prognosis of patients with AML with the risk score model to construct a nomogram Fig. I. By calAmong the 32 SFs, we observed that the expression of SRSF12 and SRSF10 was most significantly upregulated in AML. Based on the low expression of SRSF12 and its prognostic protection factor, we only conducted an in-depth study on the risk factor SRSF10 to explore its relationship with the onset and development of AML. The up-regulated expression of SRSF10 in AML samples of the TCGA database and normal blood samples of the GTEx database is shown in Fig. To further clarify the biological role of SRSF10 in the development of AML, we obtained cDNA containing SRSF10 sequence and a plasmid targeting shRNA, which were packaged with lentivirus, followed by infection of the AML cell line THP-1. Stably transfected cell lines with SRSF10 overexpression (oeSRSF10) and knockdown (shSRSF10) were screened. As shown in Fig. The proliferation of THP-1 cells was detected by CCK8 assay and EdU assay after SRSF10 overexpression and knockdown. CCK8 assay showed that compared with the control-oeSRSF10 group, the proliferation ability of THP-1 cells in the SRSF10-oe group was significantly enhanced. Compared with the control-shSRSF10 group, the proliferation of THP-1 cells in the SRSF10-SH1 and SRSF10-SH2 groups was significantly reduced Fig. G. EdU stWe used Annexin V-FITC/PI staining to label apoptotic cells. Apoptosis in control-shSRSF10, SRSF10-SH1, and SRSF10-SH2 groups were detected by flow cytometry. The apoptosis rate of the SRSF10-SH1 and SRSF10-SH2 groups was higher than that of the control group Fig. J. The apExamination of the mechanism and treatment of AML remains a challenging issue . AlthougThe role of abnormal splicing of genes in AML progression and drug resistance has garnered interest, and studies have shown that recurrent SF mutations are important drivers of hematological malignancies . AS is aThis study explored SFs with the most extensive and prominent functions in the hnRNP and SR families. Mutations and abnormal expression of SFs can influence the expression changes of different subtypes of many genes, which may have completely different functions. For example, the Bcl-2 family generates pro-apoptotic and anti-apoptotic components through AS . We explTumor classification is a method used to distinguish the degree of malignancy and heterogeneity of tumors. Classification according to the individual characteristics of different patients is helpful for clinical diagnosis, treatment, and prognosis evaluation. We performed a clustering analysis based on the expression of SFs and identified four splicing regulation patterns in different patients with AML. Moreover, the biological processes of these four splicing regulation patterns are significantly different. In the pattern with generally low expression of SFs, a variety of oncogenic signal transduction pathways are significantly activated, such as KRAS, IL2/STAT5, NF-κB/TNF-α, and WNT-β/catenin pathways. Therefore, the typically low expression of SFs can be used as a signature to indicate abnormal changes in the oncogenic pathway. However, in the pattern with high expression of SFs, we observed a significant enhancement of cell proliferation signals, both the cell cycle-related pathways and the expression of genetic information, showing a highly active state, which can also be used as a signature of disease development. It is well understood that SFs are themselves involved in the regulation of transcriptome, and their high expression and proliferation-induction activity are mutually promoting. In addition, with potent cell life activities, this splicing regulation pattern also fully activates DNA damage repair-related signal pathways to ensure the normal expression of genetic information. The expression of SFs in the other two splicing regulation patterns was not as consistent as the first two patterns, but the difference in prognosis between the two groups was the most apparent. When the expression level of SFs is between the first two patterns, the prognosis of patients was the worst. In this splicing regulation pattern, we observed a significant increase in the infiltration rate of inflammatory immune cells such as monocytes, M2 macrophages, and neutrophils, and a high expression level of immune checkpoints, suggesting a tumor microenvironment with chronic inflammatory development and immunosuppression, corresponding to various pro-inflammatory and immune-related signaling pathways, such as B-cell receptors, chemokines, NOD-like receptors, and Toll-like receptors signaling pathways. In the splicing regulation pattern with the best prognosis, most of the prognostic risk-associated SFs were underexpressed, while SFs with protective effects and association with a positive prognosis, such as SRSF12 and HNRNPH1, were significantly overexpressed. These expressive features indicate the benefits of survival. In this pattern, the anti-tumor immunity mediated by T cells may play an important role, which is more conducive to the survival of patients.Splicing regulation patterns can be used for tumor classification to better elucidate the pathological status and tumor microenvironment characteristics of patients with AML. To better guide the development of personalized treatment plans and prognosis evaluations of patients with AML, we also predicted the treatment sensitivity of patients with different splicing regulation patterns. Patients with splicing regulation patterns with generally high expression of SFs were more sensitive to cytarabine, doxorubicin, and midostaurin. Patients with the best survival splicing regulation pattern also benefited from cytarabine. In the prediction of immunotherapy response, patients with splicing regulation pattern with moderate expression level of SFs and showing the worst prognosis had a higher response to anti-PD-1 treatment. In addition, the prognostic risk score model can accurately predict the prognosis of patients with AML. The nomogram constructed by combining age and cytogenetic risk can better predict the OS of patients, which can be used as a prognostic prediction tool to help clinicians better evaluate the prognosis of patients.Finally, we investigated the cancer-promoting mechanism of SRSF10 in AML. SRSF10 is highly expressed in many cancers and plays a cancer-promoting role. For instance, it promotes the production of the cancer-promoting splice variant BCLAF1-L . It reguIn summary, this study analyzed the expression landscape of SF families represented by hnRNP and SR through multi omics data. The splicing regulation patterns identified based on SF expression are significantly different in many biological processes and immune characteristics. The recognition of these patterns has potential reference value for the evaluation of tumor microenvironment and clinical results of patients with AML. These findings provide a new perspective for the establishment of personalized therapy. However, this study also has some limitations. First, there is a lack of larger sample data and clinical reality cohort to verify the characteristics of splicing regulation patterns. Second, we only explored the relationship between SRSF10 and the malignant phenotype of AML cells. More efforts are still needed to explore broader SFs and more detailed splicing regulation mechanisms.This study revealed the expression characteristics of hnRNP and SR families SFs in AML, as well as the differences in biological processes and clinicopathological factors of different splicing regulation patterns. The analysis based on splicing regulation patterns can promote our understanding of the relationship between tumor microenvironment and AS in AML, which can aid in the development of clinical personalized treatment plans. Meanwhile, the prognostic risk score model can accurately predict the prognosis of patients with AML. In subsequent experimental analysis, we confirmed that SRSF10 promoted the development of malignant phenotype in AML cells, suggesting that SRSF10 could be used as a potential therapeutic target and biomarker for AML.Additional file 1: Figure S1. Correlation analysis of splicing factor expression and prognosis of AML patients (A), Kaplan-Meier curve analysis between groups with high and low expression of splicing factor (B).Additional file 2: Table S1. Genes and coefficients of risk score model.


AtCAX1 activity is inhibited by its N-terminal regulatory region (NRR), which was initially defined as the sequence between the first two methionines. However, the accuracy of this NRR definition and the NRR regulatory mechanism remain unclear. Here, using tomato SlCAX1 as a model, we redefined the NRR of CAXs and demonstrated that our new definition is also applicable to Arabidopsis AtCAX1 and AtCAX3. The N-terminal-truncated SlCAX1 (SlCAX1Δ39) but not the full-length SlCAX1 was active in yeast, similar to Arabidopsis AtCAX1. Characterization of slcax1 mutants generated by CRISPR-Cas9 confirmed the calcium transport ability of SlCAX1. Sequence alignment between SlCAX1, AtCAX1, AtCAX3, and the Bacillus subtilis Ca2+/H+ antiporter protein YfkE revealed that SlCAX1 does not have the 2nd methionine and YfkE does not have any amino acid residues in front of the first transmembrane domain. Truncating the amino acid residues up to the first transmembrane of SlCAX1 (SlCAX1Δ66) further increased its activity. The same truncation had a similar effect on Arabidopsis AtCAX1 and AtCAX3. Expression of full-length SlCAX1 and SlCAX1Δ66 in tomato plants confirmed the results. Our results suggest that SlCAX1 is critical for Ca2+ homeostasis and all the amino acid residues in front of the first transmembrane domain inhibit the activity of CAXs. Our redefinition of the NRR will facilitate fine-tuning of Ca2+ partitioning to reduce the incidence of Ca2+-related physiological disorders in crops.Calcium (Ca Precise regulation of its distribution between different subcellular compartments is critical for normal plant growth, development, and adaptation to the environment. Most Ca2+ is stored in the cell wall, apoplast, vacuole, and endoplasmic reticulum and is maintained at extremely low levels in the cytosol , control the efflux of Ca2+ from the cytosol. This establishes a Ca2+ gradient between the cytosol and other compartments and maintains Ca2+ partitioning in plant cells , complements the hypersensitivity of the yeast mutant strain to calcium, suggesting that the first 36 amino acid residues inhibit AtCAX1 activity. The region deleted in AtCAX1Δ36 was defined as the NRR (Δ36) is as active as AtCAX1Δ36 in yeast expression assays. However, when longer truncations are performed, AtCAX3 is able to transport Ca2+ in both yeast and plants , which is 36 amino acids long . The NRR the NRR . AtCAX3 d plants . Furtherimpaired , suggest2+ homeostasis, tremendous effort has been made to ectopically express these genes in different economically important species, such as tomatoes, potatoes, and carrots, with the aim of improving fruit quality, abiotic stress tolerance, or shelf life, or alleviating Ca2+-related physiological disorders , which lacks the vacuolar Ca2+-ATPase (PMC1) and vacuolar Ca2+/H+ antiporter (VCX1), was provided by Dr. Kendal Hirschi (Solanum lycopersicum “Rubion”) were grown on 1/2 Murashige and Skoog (MS) medium for 2 weeks and then transferred onto an equal volume of solution containing the different metal ions and incubated for 16 h. The tissues were rinsed with distilled water three times and dried on tissue paper before flash freezing with liquid nitrogen. The frozen tissues were kept at −80°C before analysis.Yeast strain K667 ( Hirschi . For metSlCAX expression. First-strand cDNA was produced using the iScript™ cDNA Synthesis kit from BIO-RAD. The first-strand cDNA of 1 μl was used to amplify SlCAX-specific fragments and SlACTIN (acc. no. TC194780) was used as a control. Specific amplification primers are shown in RNA was isolated using the RNeasy Plant Kit (Zymo Research), according to the manufacturer’s instructions. RT-qPCR was performed to detect SlCAX  and AtCAX  genes were amplified from the tomato and Arabidopsis cDNA libraries, respectively, and cloned into the yeast expression vector piHGpd  following a previously described method (1 vector . Primer d method . The traslcax1 knockouts in tomato (Micro-Tom) through Agrobacterium-mediated transformation. We designed two guide RNAs (gRNAs) targeting the coding region of SlCAX1. The sequence of Guide1 was ‘TCG TAG CCA TGG ACG AAC GG’ and that of Guide2 was ‘CTT CTA AAT GCA ACA TGT GG’. The two guides were cloned into the CRISPR-Cas9 vector BGK012, which was provided by Jiangsu Baige Gene. The vector map is shown in Agrobacterium strain LBA4404 and then into tomato, as described , and the pH was adjusted to 5.8–6.0 with KOH. After 4 weeks, plants of similar size from each of the lines were harvested and rinsed with deionized water two to three times before drying with filter paper  of the er paper . The platroscopy .Arabidopsis AtCAX1 protein sequence as query. We identified six proteins with high similarity to Arabidopsis AtCAX1 . Phylogenetic analysis using the Neighbour-Joining method identified two tomato proteins (Solyc09g005260 and Solyc06g006110) in the same clade as AtCAX1, AtCAX3, and AtCAX4, which we named SlCAX1 and SlCAX3, respectively , which has defects in vacuolar Ca2+ transport , and AtCAX1 is activated upon the phosphorylation , and double mutants show synergistic phenotypes , National Natural Science Foundation of China (32171925 and U21A20210), and Innovation Program of Chinese Academy of Agricultural Sciences (GJ2022-14-5 and CAAS-ZDRW202004). The open access publication fees will be from Innovation Program of Chinese Academy of Agricultural Sciences (GJ2022-14-5).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


To analyze the relationship between negative lymph node (LNneg) size as a possible surrogate marker of the host antitumor immune response and overall survival (OS) in esophageal cancer (EC) patients.Lymph node (LN) status is a well-established prognostic factor in EC patients. An increased number of LNnegs is related to better survival in EC. Follicular hyperplasia in LNneg is associated with better survival in cancer-bearing mice and might explain increased LN size.The long axis of 304 LNnegs was measured in hematoxylin-eosin stained sections from resection specimens of 367 OE02 trial patients , 179 with neoadjuvant chemotherapy plus surgery (C+S)) as a surrogate of LN size. The relationship between LNneg size, LNneg microarchitecture, clinicopathological variables, and OS was analyzed.P = 0.01) and lower frequency of lymphatic invasion (P = 0.02) in S patients only. Irrespective of treatment, (y)pN0 patients with large LNneg had the best OS. (y)pN1 patients had the poorest OS irrespective of LNneg size (P < 0.001). Large LNneg contained less lymphocytes (P = 0.02) and had a higher germinal centers/lymphocyte ratio (P = 0.05).Large LNneg size was related to lower pN category pN0 EC patients. Future studies need to confirm our results and explore underlying biological mechanisms. Hematoxylin/eosin slides and paraffin blocks from the resection specimen were collected retrospectively. Slides with LNs were available from 179 C+S patients and 188 S patients for analyses .In the UK MRC OE02 trial, 802 patients with histologically or cytologically confirmed, locally advanced resectable EC were randomized to treatment by surgery alone (S patients) or neoadjuvant chemotherapy consisting of 2 cycles of 5-fluorouracil and cisplatin followed by surgery (C+S patients) between 1992 and 1998.29 depth of invasion ((y)pT category) and LN status ((y)pN category) were established during central histopathology review or extracted from the original pathology reports  and classified according to Union for International Cancer Control (UICC) Tumour Node Metastasis (TNM) classification 6th edition.30 Clinical outcome data were extracted from the UK MRC OE02 clinical trial database. The study was approved by the South East Research Ethics Committee, London, UK, REC reference: 07/H1102/111.Clinicopathological data of this subset of OE02 trial patients such as histological tumor type, grade of tumor differentiation, tumor regression grade according to Mandard classification,The clinicopathological data from our study cohort were compared to all OE02 trial patients who had a resection to confirm the representativeness of our subset.Hematoxylin/eosin stained slides with tumor free regional LNs (LNneg) were available from 159 C+S patients and 145 S patients. Regional LNs with tumor metastasis (LNpos) were available from 110 C+S patients and 126 S patients .31 An irregular border was also regarded as the outline of the LN. Two aggregates of lymphoid tissue were considered as one LN if they were less than 1 mm apart or were present in the same piece of fatty tissue on the same slide . LNnegs with signs of tumor regression such as fibrosis or mucin lakes without viable tumor cells which therefore must have been tumor positive before treatment (n = 12), were excluded from analysis.A LN was defined as any size of lymphoid tissue with a clearly identifiable capsule or as an aggregate of lymphoid tissue without capsule measuring >3 mm in long axis according to the LN definition of UICC TNM classification 5th ed.The LN border was manually annotated along the outer border in ImageScope using a pen tool and touch screen . Length measurement lines were placed manually using the ‘ruler tool’ and measurements in millimeter were provided by the software. The investigator drawing the LN outlines and placing the measurement lines was blinded to any clinicopathological parameters including patient treatment details. The LN status (positive vs negative), outlines and long axis lines were quality controlled by a second independent investigator.32 We used 250 measurement points ±5% tolerance for each LN . Each measurement point was manually reviewed and the tissue type at the tip of the arrow was categorized as lymphocytes , GC, histiocytes, vessels, other tissue  or noninformative  at 5× magnification . For each LNneg, the percentage of area (%area) covered with a particular microarchitecture feature was calculated as follows:To better understand the relationship between LNneg size and survival in EC patients without LN metastasis, we decided to explore the LN microarchitecture features in more detail in these patients. We quantified the LN specific microarchitectural features using point counting with random systematic sampling, a well-established technique for morphometric object quantification.Additionally, ratios of particular microarchitectural features were calculated per LNneg: %area of GC/%area of lymphocytes, %area of histiocytes/%area of lymphocytes, %area of GC/%area of histiocytes.33 The length of the LN long axis was used as a surrogate of LN size. The largest LNneg and the largest LNpos per patient were used for statistical analyses. All available samples were included. In case of missing data of LNneg or LNpos size, patients were excluded from the respective analyses.Statistical analyses were performed using SPSS statistics software  and R (version 3.5.3).As we were also interested in a potential effect of neoadjuvant chemotherapy on LN size, LNpos size and LNneg size were compared within treatment arms and between treatment arms. Similarly, the relationship between LN size, histological tumor type (adenocarcinoma vs squamous cell carcinoma [SCC]), predominant grade of tumor differentiation according to WHO classification, depth of invasion ((y)pT), LN status ((y)pN), and resection margin status was investigated for LNneg and LNpos separately per treatment arm. TNM staging was calculated according to TNM classification 6th ed. as this was the TNM classification valid at the time of the original trial reporting. The Kruskal-Wallis test was used to determine if statistically significant differences were present between 2 or more groups.As there were no data published which cutoff to use when analyzing the histological LN size, we initially used the radiological LN size cutoff of 10 mm for categorizing LNs as being large (≥10 mm) versus small (<10 mm).34 to the data for each treatment arm, using the R package, Hmisc.35 Splines model the relationship between size of largest LNneg and hazard ratio of 5-year OS with individual piecewise curves drawn between a selected number of knot points. The number of knots is chosen based on the number of data points available. Knot points are selected based on percentiles of LNneg size to ensure that each curve is informed from an even amount of data. The ‘restricted’ element comes from restricting the individual curves so that they must meet at the knot points to form one smooth curve across LNneg size. From this curve it can be assessed whether there is an increased or decreased hazard ratio of 5-year OS across different values of LNneg size.To assess the relationship of LNneg size and survival, we fitted a restricted cubic spline as described by Gauthier et alFor this study, a 3-knot placement for LNneg size was selected to maximize the information used to create the spline curves. These knot points would be utilized as cut-points to categorize LNneg size within the multivariate and univariate model if the relationship was found to be nonlinear. The plot resulting from this analysis allowed us to visually assess whether there was a sufficiently large difference in the relationship between LNneg size and survival between treatment arms which would make it necessary to add an interaction term to the multivariate survival model. We chose a per protocol analysis to accurately access the effects of the different treatments.The primary endpoint in this study was 5-year OS. Five-year OS was calculated from the date of surgery to the date of death or last follow up using the Kaplan-Meier method. Survival differences were assessed using log-rank statistics. As there was no survival difference between C+S and S patients in our cohort (see Result section), survival analyses were performed for the whole cohort initially.Multivariate survival analysis was performed using a Cox proportional hazard model including the covariates final treatment , (y)pT category, (y)pN status, and LNneg size. For additional analysis, the variable of the cubic spline approach and interaction treatment-LNneg size were included as covariates in the Cox proportional hazard model. Proportional hazards were tested using the Kaplan-Meier plots.In addition, we explored whether a potential survival benefit of the LNneg size could be related to LN status ((y)pN0 vs (y)pN1). For this analysis we combined LNneg size dichotomized at the median (LNneg size <7.41 mm or ≥7.41 mm) and (y)pN status and compared OS of patients with (y)pN0+ LNneg<median vs (y)pN0+LNneg≥median vs (y)pN1 + LNneg<median vs (y)pN1+LNneg≥median using the Kaplan-Meier method. The median LNneg size of all patients (including (y)pN0 and (y)pN1 patients) was 7.41 mm, which was used as a cutoff point.In the (y)pN0 patient subcohort, LN microarchitectural features (%area and ratios) were compared between patients with large LNneg (≥median LNneg size of N0 patients [8.13 mm]) and small LNneg (<8.13 mm) using Kruskal-Wallis test. A cutoff point of 8.13 mm was used as this was the median LNneg size of (y)pN0 patients. Boxplots were created to visualize the difference of the respective LN microarchitectural feature between groups of LNneg size.P values of <0.05 were considered significant. For an overview of the performed analyses, see the REMARK profile, Supplemental Digital Content Table http://links.lww.com/SLA/D443. For an overview of used cutoffs see Supplemental Digital Content Table 3, http://links.lww.com/SLA/D443.http://links.lww.com/SLA/D443 and Supplemental Digital Content Table 5, http://links.lww.com/SLA/D443, Supplemental Digital Content Figure http://links.lww.com/SLA/D443). Therefore, patients included in our study cohort were considered representative of the OE02 trial population who had a resection.The clinicopathological parameters such as age, sex, (y)pT and (y)pN stage, and OS of patients included in the current study were similar to those of all OE02 trial patients who had a resection  age of patients (n = 304) included in the current study was 62.5 years (30–83.1 years). Median (range) follow up time from surgery was 16.9months (0.06–158.1 months). Median (range) number of resected LNs per patient was 10 (1–67).http://links.lww.com/SLA/D443 for LNpos.Three hundred patients 81.7%) had died at the end of the study period. For a summary of clinicopathological data at the time of randomization and from the resection specimen stratified by LNneg size see Table .7% had dThis pilot study included 367 patients in total, 179 C+S patients and 188 S patients .The largest LNneg size was similar between C+S patients and S patients , lower pN status (P = 0.01), and lower frequency of lymphatic invasion .In S patients, a larger LNneg size was related to a lower number of LNpos P = 0.08, lower P values > 0.05, Table In C+S patients, largest LNneg size was not related to any of the clinicopathological characteristics . Largest LNpos size was not related to any of the clinicopathological characteristics neither in S patients nor in C+S patients .The size of the largest LNpos differed significantly between C+S patients and S patients , (y)pT category (P = 0.001), (y)pN status (P < 0.001), grade of primary tumor differentiation (P = 0.01) and lymphatic invasion (P < 0.001)  Table .P = 0.19) .Using the radiologically used LN size cutoff of 10 mm, there was no survival difference between patient with LNneg size ≥10 mm and LNneg size <10 mm (Hazard Ratio (HR): 1.21, 95% Confidence Interval (CI): 0.91–1.62; P = 0.017).Using the restricted cubic spline approach with 3 internal knots (see Methods), we modelled the relationship between risk of death and maximum LNneg size per treatment arm. Figure For LNneg size greater than the median, the spline curves Fig.  begin toAlthough we appreciated that both treatments showed somehow similar trends in their splines with respect to survival and despite confidence intervals were largely overlapping, the distance between the curves of S and C+S patients was felt to be sufficiently big enough to justify including an interaction term for treatment within the multivariate model. The 3 internal knots were used as cut-points to categorize the LNneg size variable into 3 groups within the multivariate survival models to reflect the difference across the knot groups.P = 0.006) and (y)pT status  as independent prognostic variables. None of the other variables including LNneg size were significant in multivariate analysis pT status, (y)pN status, LNneg size groups by spline cut-points, and treatment interaction of LNneg groups by spline cut-points confirmed (y)pN status pN0+LNneg<median; (y)pN0+LNneg≥median; (y)pN1 + LNneg<median; (y)pN1 +LNneg≥median. Univariate survival analysis showed a significant survival difference between groups pN0 patients might be related to the better survival of some of the ypN0 patients, we analyzed the LN microarchitecture features of (y)pN0 patients and their relationship with LNneg size.P = 0.02 . The %area of GCs was higher in (y)pN0 patients with large LNneg, although not reaching statistical significance . The %area containing histiocytes did not differ between patients with small and large LNneg . The GCs/lymphocytes ratio was higher in patients with large LNneg with borderline significance , suggesting that large LNnegs may have increased formation of GC structures compared to small LNnegs pN0 patients with small LNneg (LNneg size <8.13 mm), the median percentage of LN area (%area) with lymphocytes was 61.1% (range: 22.6%–84.6%) compared to 50.9% (range: 10.3%–75.3%) in (y)pN0 patients with large LNneg (LNneg size ≥8.13 mm), 23Research aiming to identify new potential prognostic or predictive biomarker has mainly focused on the primary tumor or on the number of positive LNs, although the potential prognostic impact of features that characterize LNs without metastasis has not been investigated in detail in patients with EC. Earlier studies in colorectal cancer suggested that the size of the LNneg could be an indicator of increased host antitumor immune response and could be related to a survival advantage.36 We found that patients with large LNneg in the resected specimen survived significantly longer than patients with small LNneg. Thus, this is the first study to suggest a potential prognostic role of LNneg size in EC patients irrespective of treatment modality or histological tumor type. Our EC results are concordant with previous findings reported in colorectal and gastric cancer.38The current study aimed to explore the relationship between the LN size and prognosis in EC patients from the UK MRC OE02 trial treated with surgery alone (S patients) or neoadjuvant chemotherapy followed by surgery (C+S patients). We used the length of the long axis of a LN as surrogate of LN size. Overall, the LN sizes in our study were similar to that found by others.6 Although LNneg size was not an independent prognostic marker in multivariate analysis, our exploratory analysis combining the LNneg size with the LN status revealed that (y)pN0 EC patients with large LNneg have a better survival than (y)pN0 EC patients with small LNneg. This could potentially suggest that the LNneg size might be a clinically useful marker to identify (y)pN0 patients who may benefit from further adjuvant treatment.LN status (pN) is known to be one of the most important prognostic factors in EC patients, more important than primary tumor regression grade as we showed in a previous study in the OE02 trial patients.40 It has been shown that secondary follicles not only become hyperplastic but may also develop GCs and enlarge their underlying dendritic network possibly explaining the overall changes in LN size during immune response activation.43 Our pilot study of the LN microarchitecture found that large LNnegs in (y)pN0 patients have significantly less lymphocytes located outside of GCs and a higher ratio of GCs to lymphocytes confirming studies showing immune response leading to LN size changes.45 This could possibly provide an explanation for the improved OS of (y)pN0 patients with large LNneg.Size changes in regional LNneg in pancreatic cancer and colorectal cancer patients have been related to an increased host antitumor immune response resulting in follicular hyperplasia with the formation of GCs, proliferation of lymphocytes in the medullary or paracortical area and/or sinus histiocytosis due to incoming tumor derived antigens.46 Unfortunately, LN size measurements were not included in this study, so results cannot be directly compared with our findings.46 In the current study in EC patients, we found a relationship between large regional LNneg and lower number of LNpos. However, related to the relatively small number of patients in subgroups, we are unable to distinguish between a survival benefit related to enlarged LNneg  and a survival benefit due to overall lower metastatic burden.A retrospective study in colorectal cancer suggested that a higher number of LNneg might be related to an increased lymphocyte infiltration in the primary tumor and better survival.19 Indeed, LNneg size was found to be increased in rectal cancer patients treated with chemoradiotherapy, compared to patients treated with surgery alone.47 In contrast, Schröder et al48 did not find a difference in LNneg size when comparing LNneg size in a small series of EC SCC patients treated with either surgery alone or chemoradiotherapy. It should be emphasized that the aforementioned 2 studies combined chemotherapy with radiotherapy which makes direct comparison to our findings difficult.To the best of our knowledge, the effect of chemotherapy on the histological size of regional LNneg has not been investigated in EC resection specimens. As the OE02 trial had a surgery alone arm and a chemotherapy plus surgery arm, we were able to assess whether neoadjuvant chemotherapy induces a change in the size of the LNneg and whether the prognostic value of the LNneg size was different between treatment arms. To our surprise, neither LNneg size nor prognostic value of large LNneg size were different between treatment arms. We had expected that due to the chemotherapy induced immunogenic cell death, LNneg size would increase.36 LN sizes can also increase in case of an infection, clinical data to this effect is unavailable but presence of an infection could have influenced our results. The total number of resected LNs found per patient would be considered relatively low compared to current standards. This could be related to the LN dissection by the surgeon and/or pathologist, as the type of lymphadenectomy is unknown but also to the unavailability of the slides to us after such a long time of material storage. We chose to analyze the largest LN size when patients had multiple LNs assuming that large LNs are more likely resected and found in the resected specimen by the pathologist than small ones. A larger number of LNs for all patients might have allowed a more detailed analysis of the effect of number of large LNs or combination of large LNneg with LNpos sizes. Unfortunately, data on the LNneg location were not available consequently we could not relate this to the tumor location. Future analysis in larger groups of patients including LNpos is needed.The current study has some limitations. We used retrospectively collected material from a trial which recruited EC patients between 1992 and 1998. The OE02 trial protocol did not include specific guidance for the surgeons, regarding the type of LN dissections nor for the pathologist, on handling the resection specimen. We therefore had to assume that it was common practice to cut through the center of the LN at the time of specimen cut up by pathologists. Reassuringly, the LN sizes measured in the current study are comparable to those reported by others in more recent studies.In summary, this pilot study using resection material from EC patients randomized to the OE02 trial provides first insights into the potential importance of assessing LNneg size to predict prognosis in EC patients and in particular to identify EC patients with (y)pN0 status with a poorer prognosis who might benefit from additional postsurgical therapy. Our results require validation in an independent cohort and further studies to better understand the underlying biological mechanism of increased LNneg size in some patients. Based on our results, we hypothesize that large regional LNneg size identified at the time of diagnosis might be a potential clinically useful marker for the identification of highly immunogenic EC. Thus, there is a clinical need to improve radiological staging of LNs and in particular recognition of LNneg. This might be achieved in the first instance by combining pathology-based LN size studies with matched radiological imaging studies at the time of surgery to translate histological findings into patient management decisions in the future and personalize risk-stratification in EC patients.


Extramedullary manifestations (EM) are rare in acute myeloid leukemia (AML) and their impact on clinical outcomes is controversially discussed.We retrospectively analyzed a large multi-center cohort of 1583 newly diagnosed AML patients, of whom 225 (14.21%) had EM.p < 0.0001), peripheral blood blasts (p < 0.0001), bone marrow blasts (p = 0.019), and LDH (p < 0.0001). Regarding molecular genetics, EM AML was associated with mutations of NPM1 , FLT3-ITD  and PTPN11 . With regard to clinical outcomes, EM AML patients were less likely to achieve complete remissions , and had a higher early death rate . Multivariable analysis revealed EM as an independent risk factor for reduced overall survival , however, for patients who received allogeneic hematopoietic cell transplantation (HCT) survival did not differ. For patients bearing EM AML, multivariable analysis unveiled mutated TP53 and IKZF1 as independent risk factors for reduced event-free  and overall survival .AML patients with EM presented with significantly higher counts of white blood cells (Our analysis represents one of the largest cohorts of EM AML and establishes key molecular markers linked to EM, providing new evidence that EM is associated with adverse risk in AML and may warrant allogeneic HCT in eligible patients with EM.The online version contains supplementary material available at 10.1186/s13045-022-01267-7. Extramedullary manifestation (EM) of infiltrating clonal blast populations in a variety of organs and tissues in acute myeloid leukemia (AML) is defined as a distinct entity in the 2016 WHO classification of myeloid neoplasms, myeloid sarcoma ) and canPrevious reports have estimated EM to be present in 2–9% of AML cases –8. HowevWe here present a large multi-center cohort of newly diagnosed and intensively treated AML patients to compare cytogenetic and molecular profiles as well as clinical presentations and outcomes between AML presenting with concurrent EM and non-EM AML.30) was defined as death from any cause within 30 days after initial diagnosis. EM AML status was determined at baseline by clinical examination for the entire cohort. Additional histopathologic confirmation of EM in the respective organ was available in 38 cases. The investigation was carried out under the auspices of the SAL registry and received approval of the Institutional Review Board of the Technical University Dresden (EK 98032010). Written informed consent was obtained from all participants according to the Declaration of Helsinki.We analyzed 1583 adult patients with newly diagnosed AML from previous multi-center clinical trials . Molecular profiling was done using high resolution fragment analysis for FLT3-ITD , NPM1 . In contrast to the overall patient cohort, survival rates of patients harboring EM AML compared to those who did not present with EM did not differ  of patients received an allogeneic hematopoietic cell transplantation, of whom 66 (11.52%) had EM AML. In a post-transplant setting, relapse rates did not differ between patients with and without EM AML  and OS  were significantly prolonged for ELN intermediate EM AML patients who received HCT. Finally for EM AML patients in the ELN2017 adverse risk group, again both EFS  and OS  were significantly longer for patients who received HCT compared to patients who did not receive HCT while RFS did not differ. Table Further, we analyzed patients harboring EM by ELN2017 subgroup with regard to the impact of HCT. For EM AML patients in the ELN2017 favorable risk group, we found no significant difference between patients who received or who did not receive HCT with respect to EFS, RFS, and OS. For EM AML patients in the ELN2017 intermediate risk group, RFS did not differ between patients who received or did not receive HCT. However, EFS  which functions as a signal enhancer for cell growth and differentiation downstream of numerous intracellular pathways including RAS/ERK/MAPK, JAK/STAT as well as PI3K/AKT and FLT3 signaling therefore playing a critical role in leukemogenesis [CEBPA were associated with significantly decreased odds of EM AML in our cohort, this effect was not seen individually in biallelic mutations of CEBPA, CEBPA-TAD or CEBPA-bZIP, rendering the mechanism unclear and thereby calling for more detailed investigations as subtypes of CEBPA have been reported to show differences in clinical outcomes [For cytogenetics, previous reports in smaller cohorts and case series have linked the occurrence of EM AML with cytogenetic aberrations like t , 24, trio et al.  report 1i et al.  reportedr et al.  reportedi et al.  also ideand EZH2  as well d DNMT3A  in EM AMe in AML , 35 and e in AML . PTPN11 ogenesis –41. Howe30 were significantly increased. Although EFS and RFS did not differ between patients with EM AML and non-EM AML when all patients including clinical and histological diagnosis of EM where investigated (Fig. 18FDG-PET [TP53 and IKZF1 mutations to be independently associated with reduced EFS and OS. While mutated TP53 is an established marker of adverse risk in AML in general [IKZF1 alterations is far less well understood in AML than it is in acute lymphoblastic leukemia [IKZF1-alterations have been recently identified in patients with blastic plasmocytoid dendritic cell neoplasms, a rare hematological disease associated with cutaneous and solid organ infiltration and poor prognosis [With respect to clinical outcome, the impact of EM in AML is still controversial. In a retrospective analysis of 3240 AML patients, Ganzel et al.  found 238FDG-PET  and thus8FDG-PET , while n general , the rolleukemia , 48. Intrognosis . Furtherrognosis  and relarognosis –53. In lrognosis . PossiblNPM1, PTPN11 and FLT3-ITD while it was less frequent in AML with mutated IDH2 or CEBPA. For patients harboring EM AML, mutations in TP53 and IKZF1 were found to be independently associated with poor outcome. In multivariable analysis, EM represented an independent marker of reduced OS. However, survival did not differ between patients with or without EM who received HCT suggesting an important role of allogeneic transplantation in the management of EM AML.We analyzed a large cohort of AML patients according to the molecular and cytogenetic profiles of EM AML and its impact on survival. We found EM AML to be significantly associated with AML-M5 as well as mutations of Additional file 1: Impact of continuous variables on odds of EM manifestation and  multivariable analysis for outcome.