Predictive Biomarkers Of Response Research Articles

Blood-based tumor mutational burden impacts clinical outcomes of immune checkpoint inhibitor treated breast and prostate cancers

BackgroundBreast and prostate tumors are known to be less responsive to immune checkpoint inhibitors (ICIs). Tissue-based tumor mutation burden (tTMB) has emerged as a predictive biomarker of response to ICIs, including in these “cold tumors”. In clinical practice, when tTMB is not available, blood-based TMB score (bTMB) can be used to consider treatment with ICIs.MethodsThis retrospective, real-world study included a final cohort of metastatic breast and prostate cancer patients treated with an ICI following a liquid biopsy test. Multiple bTMB-High cut-offs were assessed. Clinical, genomic, and outcomes data were collected. We hypothesized that a cut-off of bTMB ≥10 mut/Mb is not a strong predictor of response to ICIs in this setting. The Guardant Health genomic database (GHGD) was then queried (N = 13,992) for associations of bTMB with genomic alterations.ResultsIn the clinical cohort (N = 48), ICI treatment is offered after a median of 3 (1–9) lines of treatment. The median bTMB is 16.4 (10–186) mut/Mb. The median time on ICI and PFS is 2.1 (0–1.7) and 3.1 months (95%CI, 1.6–4.6) respectively; no difference by MSI/MMR status (p = 0.152). Response rate among eligible patients (n = 36) is 16.7%; only N = 1/6 in bTMB <16 mut/Mb. High bMSI is associated with higher bTMB (correlation test, r = 0.66, p = 0.000). In the GHGD, patients with bTMB high have significantly more alterations than bTMB low and TP53, PIK3CA, ATM, ESR1, NF1, BRCA2, ARID1A, and APC were the most frequently altered genes.ConclusionsIn this study, the practice of offering an ICIs based on bTMB was uncommon and did not independently predict ICI benefits in patients with refractory, advanced breast and prostate cancers.

SLC12A9 is an immunological and prognostic biomarker for glioma

BackgroundGlioma is one of the most common malignant brain tumors. It has a high rate of progression and a poor prognosis, and effective biomarkers still need to be identified. The solute carrier family 12 (SLC12) family has been reported to be involved in various physiological and pathological processes, but their functional roles in glioma remain unclear. MethodsUsing public datasets, we studied the mutation and expression level of SLC12 family genes in glioma and identified the significantly differentially expressed member solute carrier family 12 member 9 (SLC12A9). We further predicted the prognostic role of SLC12A9 in glioma by using the Kaplan–Meier method and Cox regression analysis. Then, we performed biological functional enrichment analysis. We focused on the relationships between SLC12A9 expression and immune infiltration in glioma. Meanwhile, we conducted in vitro experiments to evaluate the effect of SLC12A9 expression on glioma cells. ResultsAmong the members of the SLC12 family, SLC12A9 had the highest mutation rate in glioma, with gene amplification as the major mutation type, and its expression was significantly upregulated in glioma. Higher SLC12A9 expression was significantly associated with older age, higher grade, wild-type isocitrate dehydrogenase (IDH), and a worse prognosis. The functional enrichment analysis indicated that SLC12A9 is mainly related to ion channel annotation. Gene set enrichment analysis (GSEA) revealed that SLC12A9 was mainly related to the DNA replication pathway. Furthermore, we found that SLC12A9 correlated with tumor-infiltrating immune cells and immune checkpoints. Thus, SLC12A9 may be involved in regulating the immune response of glioma. Finally, our in vitro experiments revealed that silencing SLC12A9 dramatically inhibited glioma cell growth and migration. ConclusionsWe showed that SLC12A9 may be a new predictive biomarker for glioma diagnosis, prognosis, and immunotherapy response, offering helpful guidelines to advance glioma treatment.

Potential biomarkers for MCL1 inhibitor sensitivity

MCL1 is an anti-apoptotic member of the BCL2 protein family, and its overexpression is associated with poor prognosis across various cancers. Small molecule inhibitors targeting MCL1 are currently in clinical trials for TNBC and other malignancies. However, one major challenge in the clinical application of MCL1 inhibitors is the inherent or acquired resistance to these drugs. Additionally, there is a lack of predictive biomarkers to identify which tumors will respond to MCL1 inhibition. We identified a four-gene functional signature that promotes MCL1 inhibitor resistance in TNBC cells. This gene signature (GS) can distinguish resistant from sensitive TNBC cell lines. Factors encoded by these four genes promote MCL1 inhibitor resistance at least in part through regulation of the ERK signaling pathway. This mechanism involves the upregulation of BCL2 and the downregulation of BIM, which contribute to the inhibitor resistance. Thus, we have discovered a functional GS that drives MCL1 inhibitor resistance. Currently, the MCL1 inhibitor GS-9716 is in clinical trials for TNBC therapy. If validated in clinical samples, this GS could potentially serve as a predictive biomarker for therapy response and help guide the selection of combination therapies to enhance the effectiveness of MCL1 inhibitors.

Abstract B016: Utilizing gene expression profiles (GEP) to assess tumor microenvironment (TME) and response to immunotherapy

Abstract Background: Despite the success of anti-PD-1/PD-L1 immunotherapies, outcomes for lung cancer patients remain suboptimal. There is a critical need to incorporate multi-omics data focused on the tumor microenvironment (TME) to enhance patient selection and treatment individualization. This study aimed to identify predictive and prognostic biomarkers of immunotherapy response by characterizing transcriptional profiles of lung adenocarcinoma patients who underwent genomic profiling at diagnosis. Methods: RNA sequencing data were obtained from 68 lung adenocarcinoma patients who underwent next-generation sequencing with CARIS at our institution. We analyzed gene expression profiles (GEP) comprising 18 inflammatory genes associated with antigen presentation, chemokine expression, cytolytic activity, and adaptive immune resistance, identified as potential biomarkers for immune checkpoint inhibitor (ICI) response (Cristescu et al., 2018). The genes included were CCL5, CD27, CD274 (PD-L1), CD276 (B7-H3), CD8A, CMKLR1, CXCL9, CXCR6, HLA-DQA1, HLA-DRB1, HLA-E, IDO1, LAG3, NKG7, PDCD1LG2 (PD-L2), PSMB10, STAT1, and TIGIT. GEP scores were calculated, and hierarchical clustering identified tumor subsets with similar GEPs. Gene set variation analysis was conducted to assess enrichment of cell-cell interaction activities of specific ligand-receptor pairs of immune checkpoint genes, partially overlapping with the 18 GEP genes. Results: Hierarchical clustering identified four distinct GEP clusters: "T cell-inflamed GEP," "T cell-non-inflamed GEP high," "T cell-non-inflamed GEP medium," and "T cell-non-inflamed low GEP," with average scores of 0.18 (N=9, 13%), 0.11 (N=29, 43%), 0.08 (N=19, 28%), and 0.04 (N=11, 16%), respectively. The gene scores among these clusters showed significant differences (P = 3.3e-09). Additionally, analysis of specific ligand-receptor pairs of immune checkpoint genes (PD1/PD-L1, PD-L2; CTLA4/CD28, CD80, CD86; ICOS/ICOSLG; TIM3/GAL9; SIRP1/CD47) showed consistent positive enrichment in the “T cell-inflamed” cluster, with no or negative enrichment in the “T cell-non-inflamed” clusters. This suggests active immune checkpoint interactions in clusters with high GEP scores. Conclusion: We identified four different clusters among tissues from patients with NSCLC based on GEP scoring highlighting differences in immune activation and TME makeup, which may play a role in predicting response to immunotherapies. Our results suggest that GEP may provide information on identifying optimal immunotherapeutic approaches based on TME. Our findings underscore the importance of using biomarker-guided strategies to improve patient selection for precision immunotherapy approaches in lung cancer. Citation Format: Changde Cheng, Doug Welsch, Kayla F. Goliwas, Jessy Deshane, Sameer Deshmukh, Sanad Ahlushki, Yanis Boumber, Darshan Shimoga Chandrashekar, Alexander C. Mackinnon, Aakash Desai. Utilizing gene expression profiles (GEP) to assess tumor microenvironment (TME) and response to immunotherapy [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B016.

Abstract C044: Single cell RNA-sequencing coupled with lineage tracing identifies novel clonal populations associated with immunotherapy resistance

Abstract Although immune checkpoint inhibitors (ICIs) have revolutionized melanoma treatment, many individuals either show no response or eventually develop acquired resistance. This variability could be linked to differences in the tumor immune microenvironment, pre-existing drug-resistant cells or treatment induced changes in melanoma cell states. Using single cell RNA sequencing (scRNA-seq) coupled with heritable barcodes, this study aims to lineage trace changes in melanoma transcriptional cell states and map changes in the tumor immune microenvironment to uncover if preexisting and/or therapy-induced melanoma transcriptional cell states lead to resistance to ICIs. In this study, we used YUMMER1.7 mouse melanoma cells which were transduced with barcodes under conditions that allow delivery of a single unique barcode to each cell, this served as a cell lineage tag. Each barcode is heritable and stably transcribed into RNA molecules so that individual barcoded cells can be matched with a gene expression profile from scRNA-seq outputs. The barcoded cells were subcutaneously injected into C57BL/6 mice, and once tumors were established, mice were treated with 3 cycles of anti-PD-1 and anti-CTLA-4 therapy. Lineage tracing and scRNA-seq analyses were performed on tumors harvested prior to treatment, early on treatment (Day 6), during minimal residual disease (Day 13) and upon relapse. Early on treatment (Day 6)- two tumour groups were harvested, those that responded well and others that only partially responded. Our results showed that during the early on treatment phase (Day 6) tumors that responded well and those that only partially responded displayed distinct barcodes. Additionally, prevalent barcoded cells identified at the minimal residual disease phase were also dominant upon relapse. Analysis of the transcriptional states is underway to determine if ICI therapy induces transcriptional heterogeneity in sensitive and tolerant cells and if a particular or several transcriptional states lead to relapse. This study will potentially identify predictive response biomarkers and vulnerabilities of ICI naïve and resistant cells that could be targeted to improve outcomes for melanoma patients. We will also identify neoadjuvant approaches, to remove the inherent heterogeneity within the tumor cell population, facilitating a more uniform sensitivity to ICIs. Citation Format: Reem Saleh, Riyaben Patel, Dane Vassiliadis, Fayrouz Hammal, Benjamin Blyth, Xin Du, Katie Fennell, Mark A. Dawson, Grant A. McArthur, Karen Sheppard. Single cell RNA-sequencing coupled with lineage tracing identifies novel clonal populations associated with immunotherapy resistance [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr C044.

Abstract B042: Molecular assessment of cell surface targets using integrated circulating tumor cell (CTC) RNAseq and single CTC phenotyping

Abstract Background: Androgen-targeted therapies are a mainstay of treatment for metastatic prostate cancer and have significantly improved patient outcomes. However, development of treatment resistance remains universal, occurring through androgen receptor (AR) alterations driving constitutive AR signaling, or lineage state transitions that bypass AR entirely and culminate in a small cell/neuroendocrine phenotype (NEPC). Cell surface targeted therapies, including antibody drug conjugates and targeted radioligand therapies, represent a new therapeutic class that has shown promise for treatment of androgen-resistant metastatic prostate cancer (mCRPC). Circulating tumor cells (CTCs) present an accessible source of tumor material to identify expression of known and novel targets for therapeutic development, as well as the unique potential for longitudinal profiling to understand the evolution of target expression and association with clinical resistance to cell surface targeted therapies. We have developed a CTC platform allowing for gene expression and protein profiling of cell surface targets on CTCs. Methods: Live CTCs were isolated with our automated microfluidic technology integrating negative and positive selection for CTC enrichment with a cohort of 273 samples. CTCs were captured immunomagnetically followed by RNA isolation on chip and RNA-seq, or protein staining on chip for single cell fluorescent quantification of prostate adenocarcinoma and NEPC cell surface targets including PSMA, TROP2, B7H3 and DLL3. Results: CTC RNA sequencing can be used to understand the expression of cell surface targets across different CTC phenotypes. In CTCs from patient with mCRPC, canonical prostate adenocarcinoma cell surface targets STEAP1, KLK2 and FOLH1 and epithelial cell surface target TACSTD2 had the highest expression, while prostate adenocarcinoma target STEAP2, pan-tumor target ERBB2, and tumor immune checkpoint cell surface protein CD276 (B7H3) had intermediate expression. Expression of DLL3 and SSTR2, targets associated with neuroendocrine differentiation, was lowest, though still detected in a subset of CRPC CTCs. Comparison of expression levels between CRPC and NEPC CTCs demonstrated lower expression of most adenocarcinoma cell surface targets in NEPC CTCs as expected, and a trend towards higher expression of DLL3 and SSTR2. Cell surface expression is being assessed for proteins including Trop-2, PSMA and DLL3. Evaluation of DLL3 at the protein level in a subset of patients including both CRPC (n=13) and NEPC (n=12) confirmed that DLL3 was detected in both adenocarcinoma and neuroendocrine CTCs, with a median of 45.8% DLL3-positive CTCs per sample. Conclusions: Biomarkers are needed to better predict response and resistance to targeted therapies. CTC RNAseq and single CTC phenotyping hold potential for predictive and on-treatment biomarkers of response to cell surface targeted therapies. Further study of mechanisms driving response and resistance can be evaluated with these biomarkers. Citation Format: Jamie M. Sperger, Marina N. Sharifi, Katherine R. Kaufmann, Matthew L. Bootsma, Shannon R. Reese, Viridiana Carreno, Alex H. Chang, Luke A. Nunamaker A. Nunamaker, Charlotte Linebarger, Amy K. Taylor, Katherine E Tippins, Kyle T. Helzer, Shuang G. Zhao, Joshua M Lang. Molecular assessment of cell surface targets using integrated circulating tumor cell (CTC) RNAseq and single CTC phenotyping [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B042.

Next-generation biomarkers for alcohol consumption and alcohol use disorder diagnosis, prognosis, and treatment: Acritical review.

This critical review summarizes the current state of omics-based biomarkers in the alcohol research field. We first provide definitions and background information on alcohol and alcohol use disorder (AUD), biomarkers, and "omic" technologies. We next summarize using (1) genetic information as risk/prognostic biomarkers for the onset of alcohol-related problems and the progression from regular drinking to problematic drinking (including AUD), (2) epigenetic information as diagnostic biomarkers for AUD and risk biomarkers for alcohol consumption, (3) transcriptomic information as diagnostic biomarkers for AUD, risk biomarkers for alcohol consumption, and (4) metabolomic information as diagnostic biomarkers for AUD, risk biomarkers for alcohol consumption, and predictive biomarkers for response to acamprosate in subjects with AUD. In the final section, the clinical implications of the findings are discussed, and recommendations are made for future research.

CTNI-44. NCT03643549 PHASE IB/II TRIAL: EFFICACY, SAFETY, AND BIOLOGICAL MECHANISMS OF OBJECTIVE RESPONSES IN RECURRENT GBM PATIENTS WITH UNMETHYLATED MGMT PROMOTER TREATED WITH SEQUENTIAL BORTEZOMIB AND TEMOZOLOMIDE

Abstract BACKGROUND Glioblastoma (GBM) is amongst the deadliest malignancies in adults, but especially for patients with unmethylated MGMT promoter (uMGMT) who gain limited benefit from the standard treatment. We previously demonstrated that proteosome inhibitor bortezomib (BTZ), inhibited NFkB activation,depleted MGMT protein and sensitized uMGMT GBM cells to Temozolomide (TMZ). Thus, a phase I/II trial testing sequential combination BTZ+TMZ was launched to investigate safety and clinical benefit. METHODS Recurrent GBM patients with uMGMT promoter, progressing ≥12 weeks after radiotherapy, KPS≥70 and radiologically measurable lesions were enrolled. The trial was powered for n=63 patients compared with n=102 historical controls. Patients received BTZ 1.3mg/m² IV on days 1, 4, and 7 of each 4-week cycle, starting on day 3 with oral 200mg/m² TMZ for 5 days/week. Whole exome sequencing (WES) of tumor DNA was conducted to identify genetic changes and LC-MS/MS used to asses proteomic changes in plasma collected during treatment. RESULTS As of January 2024, 54 patients (median 55y (25-70); 38 males, 16 females) were treated. The median KPS 90 (range 70-100) and NANO score was 1 (range 0-7). QoL was preserved, with mild /moderate adverse events. Adjusted analyses showed overall survival (OS) of 16.2 months compared to 8.4 months for uMGMT control patients, HR0.48, 95%CI[1.057-2.74],P=0.028. Objective radiological responses stable disease or better were observed in 22% (12/54) patients. Survival from recruitment was 10.5 months for responders vs. 4.8 months for rest of cohort, P=0.054 HR2.55, 95%CI[0.984-5.94]. Preliminary data indicate 78% (7/9) of responders harboured amplified EGFR vs. 38% in rest-of-the patients. The responders differentially expressed proteins critical for cellular processes, including ADAMTSL4, NCAM1, AZGP1, MMP2, CD163, and IL6ST. CONCLUSION Sequential BTZ+TMZ therapy is safe, effective and showed clinical benefit. EGFR amplification may be a predictive biomarker for response through NFκB activation, that is targeted by BTZ thereby depleting MGMT protein and enhancing treatment efficacy. Sequential BTZ+TMZ treamtment may represent additional treatment option at recurrence.

CTIM-07. A PHASE II, OPEN LABEL, SINGLE ARM STUDY OF NIVOLUMAB FOR RECURRENT OR PROGRESSIVE IDH MUTANT GLIOMAS WITH PRIOR EXPOSURE TO ALKYLATING AGENTS

Abstract BACKGROUND Somatic mutations in isocitrate dehydrogenase 1 (IDH1) are an important prognostic factor in patients with gliomas. IDH-mutant gliomas are prone to develop hypermutation after exposure to alkylating agents; in other solid tumors, hypermutation may be a predictive biomarker for PD-1 inhibitor response. In this study, we hypothesize that this specific subgroup of patients would clinically benefit from nivolumab as measured by overall response rate (ORR), duration of response (DOR), median progression-free survival (PFS), and overall survival (OS). METHODS Patients aged 18 years and older with recurrent/progressive IDH-mutant (WHO Grades 2-4) gliomas and prior exposure to alkylating agents were included. Nivolumab was given 240 mg q2w for 8 cycles, then 480 mg q4w until progression, toxicity, study withdrawal, or completion at 2 years. Efficacy was evaluated by ORR of partial (PR) and complete responses (CR) per RANO criteria; low-grade glioma RANO criteria was used for patients with non-enhancing disease. Secondary endpoints included median PFS, median OS, DOR. Toxicity and survival were followed every 3 months until death/study completion. RESULTS Thirty-three patients (66.7% male) were evaluable at study completion. Histology consisted of oligodendroglioma (N=11; 55% Grade 3) and astrocytoma (N=22; 36% Grade 3, 32% Grade 4). Median number of prior lines of systemic therapy was 1 (range 1-6). Median dexamethasone dose at screening was 0 mg (range 0-4). ORR was 9% with two PR and one CR, median DOR 33 months. 11 (32%) patients had stable disease (7 stable for 6+ months) with median PFS 2.2 months and median OS 29.1 months. There were two treatment-related Grade 3 adverse events (lymphopenia and hypotension). One patient discontinued treatment for Grade 2 transaminitis. CONCLUSIONS Though the primary endpoint was not met, three patients have ongoing CR and PR at 54+, 33+ and 24+ months. Future combination therapies with PD-1 inhibitors may increase efficacy in recurrent IDH-mutant gliomas.

BIOM-08. LEVERAGING CSF PROTEOMICS TO OPTIMIZE CNS LYMPHOMA MANAGEMENT

Abstract INTRODUCTION Despite exquisite responses to initial therapy for CNS lymphoma (CNSL), relapse is common and overall responses are disappointing compared to other non-CNS diffuse large B-cell lymphomas. Incorporation of multi-agent intraventricular chemotherapy (MAIVC) alongside systemic therapy is novel. Identification of minimally-invasive biomarkers of response to MAIVC are necessary but lacking. The objectives of this study were to 1) identify baseline cerebrospinal fluid (CSF)-based proteomic predictive biomarkers of MAIVC treatment response and 2) identify tumor burden markers for longitudinal monitoring of MAIVC treatment response in CNSL. METHODS A cohort of patients with primary or secondary CNSL that were treated with MAIVC at Penn State Health (2015-2021) was included. Each MAIVC cycle was administered via Ommaya reservoir and included a 2-drug combination comprised of methotrexate, rituximab, cytarabine, etoposide, topotecan, gemcitabine, or thiotepa. Patient-matched CSF was sampled at pre- and post-therapeutic endpoints and profiled using shotgun proteomics. Patients were grouped by treatment response status. Early responders were defined as patients that achieved malignant cell-free CSF within 6 MAIVC cycles, whereas never responders were those patients that i) did not achieve malignant cell-free CSF by endpoint or ii) required salvage surgery or radiation during MAIVC. RESULTS 59 patients were included (21 primary; 38 secondary CNSL) with a median age of 66 years (range 25-90) and median number of MAIVC cycles of 8 (range 2-23). A proteomic-based classifier, comprised of SGCE, LCP1 and AGRN, discriminated between early and never responders with an AUROC of 0.95. Comparison of CSF at baseline (&amp;lt;3 cycles MAIVC) vs. post-treatment (&amp;gt;12 cycles MAIVC) identified H3F3A, YWHAE, LCP1, CA1 and GAPDH as tumor burden biomarkers. CONCLUSION Here we developed a proteomic signature capable of predicting CNSL patient response to MAIVC, with potential to improve clinical decision making. Furthermore, the biomarkers associated with tumor burden represent important indicators of treatment response. Ongoing efforts are underway to evaluate these candidates as actionable therapeutic targets.

Decorin as a key marker of desmoplastic cancer-associated fibroblasts mediating first-line immune checkpoint blockade resistance in metastatic gastric cancer.

Gastric cancer (GC) remains a significant cause of cancer-related mortality worldwide. Despite the transformative impact of immune checkpoint blockade (ICB) therapies across various cancers, only a minority of patients with metastatic GC (mGC) benefit, emphasizing the urgent need for precise biomarkers to predict therapeutic responses and optimize patient selection. In this multi-omics study, we conducted whole exome and transcriptome sequencing on 12 tumors from mGC patients treated with nivolumab as first-line therapy. To validate our findings, we performed whole transcriptome sequencing on 17 additional tumors and analyzed 45 tumors from public dataset (PRJEB25780) of patients who received ICB therapy as second or third-line treatment. Comprehensive multi-omics analyses were conducted using single-cell RNA sequencing (n = 5, GSE167297) and spatial transcriptome sequencing (n = 2, independent internal dataset). ICB-sensitive tumors exhibited robust activation of the interferon response pathway, while ICB-resistant tumors displayed epithelial-mesenchymal transition signatures. Intriguingly, at the single-cell level, genes associated with ICB sensitivity were predominantly expressed in immune cells, whereas genes associated with resistance were primarily found in cancer-associated fibroblasts (CAFs), particularly the desmoplastic CAF (dCAF) subtype. We identified DCN as a hallmark dCAF marker, and high DCN expression was inversely correlated with PD-L1 levels, ICB resistance, and poor prognosis in mGC (log-rank p = 0.027). This study elucidates the critical influence of the tumor microenvironment, specifically dCAFs, in mediating ICB resistance in mGC. Our findings highlight DCN as a representative marker for dCAF and a promising negative predictive biomarker for ICB response. These findings highlight the complex stromal-immune interactions and open avenues for personalized treatment for mGC.

The third generation AKR1C3-activated prodrug, ACHM-025, eradicates disease in preclinical models of aggressive T-cell acute lymphoblastic leukemia

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy that expresses high levels of the enzyme aldo-keto reductase family 1 member C3 (AKR1C3). To exploit this finding, we developed a novel prodrug, ACHM-025, which is selectively activated by AKR1C3 to a nitrogen mustard DNA alkylating agent. We show that ACHM-025 has potent in vivo efficacy against T-ALL patient-derived xenografts (PDXs) and eradicated the disease in 7 PDXs. ACHM-025 was significantly more effective than cyclophosphamide both as a single agent and when used in combination with cytarabine/6-mercaptopurine. Notably, ACHM-025 in combination with nelarabine was curative when used to treat a chemoresistant T-ALL PDX in vivo. The in vivo efficacy of ACHM-025 directly correlated with AKR1C3 expression levels, providing a predictive biomarker for response. Together, our work provides strong preclinical evidence highlighting the potential of ACHM-025 as a targeted and effective therapy for aggressive forms of T-ALL.

CTR-DB 2.0: an updated cancer clinical transcriptome resource, expanding primary drug resistance and newly adding acquired resistance datasets and enhancing the discovery and validation of predictive biomarkers.

Drug resistance is a principal limiting factor in cancer treatment. CTR-DB, the Cancer Treatment Response gene signature DataBase, is the first data resource for clinical transcriptomes with cancer treatment response, and meanwhile supports various data analysis functions, providing insights into the molecular determinants of drug resistance. Here we proposed an upgraded version, CTR-DB 2.0 (http://ctrdb.ncpsb.org.cn). Around 190 up-to-date source datasets with primary resistance information (129% increase compared to version 1.0) and 13 acquired-resistant datasets (a new dataset type), covering 10 856 patient samples (111% increase), 39 cancer types (39% increase) and 346 therapeutic regimens (26% increase), have been collected. In terms of function, for the single dataset analysis and multiple-dataset comparison modules, CTR-DB 2.0 added new gene set enrichment, tumor microenvironment (TME) and signature connectivity analysis functions to help elucidate drug resistance mechanisms and their homogeneity/heterogeneity and discover candidate combinational therapies. Furthermore, biomarker-related functions were greatly extended. CTR-DB 2.0 newly supported the validation of cell types in the TME as predictive biomarkers of treatment response, especially the validation of a combinational biomarker panel and even the direct discovery of the optimal biomarker panel using user-customized CTR-DB patient samples. In addition, the analysis of users' own datasets, application programming interface and data crowdfunding were also added.

ACE2 Enhances Sensitivity to PD-L1 Blockade by Inhibiting Macrophage-Induced Immunosuppression and Angiogenesis.

Anti-PD-L1-based combination immunotherapy has become the first-line treatment for unresectable hepatocellular carcinoma (HCC). However, the objective response rate is lower than 40%, highlighting the need to identify mechanisms of tolerance to immune checkpoint inhibitors and accurate biomarkers of response. Here, we employed next-generation sequencing to analyze HCC samples from 10 patients receiving anti-PD-L1 therapy. Activation of the renin-angiotensin system was elevated in nonresponders compared with responders, and ACE2 expression was significantly downregulated in nonresponders. ACE2 deficiency promoted HCC development and anti-PD-L1 resistance, whereas ACE2 overexpression inhibited HCC progression in immune competent mice. Mass cytometry by time of flight (CyTOF) revealed that ACE2 deficient murine orthotopic tumor tissues featured elevated M2-like tumor-associated macrophages (TAMs), displayed a CCR5+PD-L1+ immunosuppressive phenotype, and exhibited high VEGFα expression. ACE2 downregulated tumor intrinsic CCL5 expression by suppressing NF-κB signaling through the ACE2/angiotensin-(1-7)/Mas receptor axis. The lower CCL5 levels led to reduced activation of the JAK-STAT3 pathway and suppressed PD-L1 and VEGFα expression in macrophages, blocking macrophage infiltration and M2-like polarization. Pharmacological targeting of CCR5 using maraviroc enhanced the tumor suppressive effect of anti-PD-L1 therapy. Together, these findings suggest that activation of the ACE2 axis overcomes the immunosuppressive microenvironment of HCC and may serve as an immunotherapeutic target and predictive biomarker of response to PD-L1 blockade.

Disruption of RNA Splicing Increases Vulnerability of Cells to DNA-PK Inhibitors.

DNA-dependent protein kinase (DNA-PK) is a key effector of non-homologous end joining (NHEJ)-mediated double-strand break (DSB) repair. Since its identification, a substantial body of evidence has demonstrated that DNA-PK is frequently overexpressed in cancer, plays a critical role in tumor development and progression, and is associated with poor prognosis in cancer patients. Recent studies have also uncovered novel functions of DNA-PK, shifting the paradigm of the role of DNA-PK in oncogenesis and renewing interest in targeting DNA-PK for cancer therapy. To gain genetic insight into the cellular pathways requiring DNA-PK activity, we used a CRISPR/Cas9 screen to identify genes in which defects cause hypersensitivity to DNA-PK inhibitors. We identified over one hundred genes involved in DNA replication, cell cycle regulation, and RNA processing that promoted cell survival when DNA-PK kinase activity was suppressed. This gene set will be useful for characterizing novel biological processes that require DNA-PK activity and identifying predictive biomarkers of response to DNA-PK inhibition in the clinic. We also validated several genes from this set and reported previously undescribed genes that modulate the response to DNA-PK inhibitors. In particular, we found that compromising the mRNA splicing pathway led to marked hypersensitivity to DNA-PK inhibition, providing a possible rationale for the combined use of splicing inhibitors and DNA-PK inhibitors for cancer therapy.

Repair-assisted damage detection as a potential predictive biomarker for immunotherapy response in ovarian cancer

Repair-assisted damage detection as a potential predictive biomarker for immunotherapy response in ovarian cancer

Utility of ctDNA as an early predictive biomarker of response to radiation in gynecologic malignancies

Utility of ctDNA as an early predictive biomarker of response to radiation in gynecologic malignancies

The Functional Transcriptomic Landscape Informs Therapeutic Strategies in Multiple Myeloma.

Several therapeutic agents have been approved for treating multiple myeloma (MM), a cancer of bone marrow resident plasma cells. Predictive biomarkers for drug response could help guide clinical strategies to optimize outcomes. Here, we present an integrated functional genomic analysis of tumor samples from MM patients that were assessed for their ex vivo drug sensitivity to 37 drugs, clinical variables, cytogenetics, mutational profiles, and transcriptomes. This analysis revealed a MM transcriptomic topology that generates "footprints" in association with ex vivo drug sensitivity that have both predictive and mechanistic applications. Validation of the transcriptomic footprints for the anti-CD38 monoclonal antibody daratumumab and the nuclear export inhibitor selinexor demonstrated that these footprints can accurately classify clinical responses. The analysis further revealed that daratumumab and selinexor have anti-correlated mechanisms of resistance, and treatment with a selinexor-based regimen immediately after a daratumumab-containing regimen was associated with improved survival in three independent clinical trials, supporting an evolutionary-based strategy involving sequential therapy. These findings suggest that this unique repository and computational framework can be leveraged to inform underlying biology and to identify therapeutic strategies to improve treatment of MM.

Microfibrillar-associated protein 4 as a predictive biomarker of treatment response in patients with chronic inflammatory diseases initiating biologics: secondary analyses based on the prospective BELIEVE cohort study.

Currently, there are no reliable biomarkers for predicting treatment response in chronic inflammatory diseases (CIDs). To determine whether serum microfibrillar-associated protein 4 (MFAP4) levels can predict the treatment response to biological therapy in patients with CIDs. The BELIEVE study was originally designed as a prospective, multi-center cohort study of 233 patients with either rheumatoid arthritis, psoriatic arthritis, psoriasis, axial spondyloarthritis, Crohn's disease, or ulcerative colitis, initiating treatment with a biologic agent (or switching to another). Clinical assessment and blood sample collection were performed at baseline and 14-16 weeks after treatment initiation. The primary analyses included participants with available blood samples at baseline; missing data were handled as non-responders. The patients were stratified into the upper tertile of serum MFAP4 (High MFAP4) versus a combined category of middle and lower tertiles (Other MFAP4). The primary outcome was the proportion of patients with clinical response to biologic therapy after 14-16 weeks. 211 patients were included in the primary analysis population. The mean age was 43.7 (SD: 14.8) years, and 120 (59%) were female. Positive treatment response was observed in 41 (59%) and 69 (49%) for High MFAP4 and Other MFAP4, respectively. When adjusting for pre-specified variables (CID, age, sex, smoking status, and BMI), the adjusted OR was 2.28 (95% CI: 1.07 to 4.85) for a positive treatment outcome in the High MFAP4 group. A high MFAP4 status before initiating biological treatment is associated with a positive clinical response, when adjusting for confounding factors.

Oxidative Phosphorylation as a Predictive Biomarker of Oxaliplatin Response in Colorectal Cancer.

Oxaliplatin is successfully used on advanced colorectal cancer to eradicate micro-metastasis, whereas its benefits in the early stages of colorectal cancer remains controversial since approximately 30% of patients experience unexpected relapses. Herein, we evaluate the efficacy of oxidative phosphorylation as a predictive biomarker of oxaliplatin response in colorectal cancer. We found that non-responding patients exhibit low oxidative phosphorylation activity, suggesting a poor prognosis. To reach this conclusion, we analyzed patient samples of individuals treated with oxaliplatin from the GSE83129 dataset, and a set of datasets validated using ROCplotter, selecting them based on their response to the drug. By analyzing multiple oxaliplatin-resistant and -sensitive cell lines, we identified oxidative phosphorylation KEGG pathways as a valuable predictive biomarker of oxaliplatin response with a high area under the curve (AUC = 0.843). Additionally, some oxidative phosphorylation-related biomarkers were validated in primary- and metastatic-derived tumorspheres, confirming the results obtained in silico. The low expression of these biomarkers is clinically relevant, indicating poor prognosis with decreased overall and relapse-free survival. This study proposes using oxidative phosphorylation-related protein expression levels as a predictor of responses to oxaliplatin-based treatments to prevent relapse and enable a more personalized therapy approach. Our results underscore the value of oxidative phosphorylation as a reliable marker for predicting the response to oxaliplatin treatment in colorectal cancer.