Biomarkers For Immune Checkpoint Inhibitors Research Articles

Immunotherapy in thymic epithelial tumors: tissue predictive biomarkers for immune checkpoint inhibitors

Thymic epithelial tumors (TETs) are rare malignant neoplasms arising in the thymus gland. Nevertheless, TETs, including thymomas (TMs), thymic carcinomas (TCs), and thymic neuroendocrine neoplasms (TNENs), are the most common mediastinal malignancies overall. A multidisciplinary approach is required for the appropriate diagnostic and therapeutic management of TETs. To date, the main therapeutic strategies are largely depended on the stage of the tumor and they include surgery with or without neoadjuvant or adjuvant therapy, represented by platinum-based chemotherapy, radiotherapy or chemoradiotherapy. Immune checkpoint inhibitors (ICIs) are ongoing under evaluation in the advanced or metastatic diseases despite the challenges related to the very low tumor mutation burden (TMB) and the high incidence of immune-related adverse events in TETs. In this regard, predictive impact of tissue biomarkers expression such as programmed cell death ligand-1 (PD-L1), and other emerging biomarkers, as well as their optimal and shared interpretation are currently under evaluation in order to predict response rates to ICIs in TETs.

Epithelial-mesenchymal transition induced by tumor cell-intrinsic PD-L1 signaling predicts a poor response to immune checkpoint inhibitors in PD-L1-high lung cancer.

We investigated the role of tumor cell-intrinsic PD-L1 signaling in the epithelial-mesenchymal transition (EMT) in non-small-cell lung cancer (NSCLC) and the role of EMT as a predictive biomarker for immune checkpoint inhibitor (ICI) therapy. PD-L1-overexpressing or PD-L1-knockdown NSCLC cells underwent RNA-seq and EMT phenotype assessment. Mouse lung cancer LLC cells were injected into nude mice. Two cohorts of patients with NSCLC undergoing ICI therapy were analyzed. RNA-seq showed that EMT pathways were enriched in PD-L1-high NSCLC cells. EMT was enhanced by PD-L1 in NSCLC cells, which was mediated by transforming growth factor-β (TGFβ). PD-L1 promoted the activation of p38-MAPK by binding to and inhibiting the protein phosphatase PPM1B, thereby increasing the TGFβ production. Tumor growth and metastasis increased in nude mice injected with PD-L1-overexpressing LLC cells. In the ICI cohort, EMT signature was higher in patients with progressive disease than in those with responses, and EMT was significantly associated with poor survival in PD-L1-high NSCLC. In PD-L1-high NSCLC, EMT was associated with increased M2-macrophage and regulatory T-cell infiltrations and decreased cytotoxic T-cell infiltration. Tumor cell-intrinsic PD-L1 function contributes to NSCLC progression by promoting EMT. EMT may predict an unfavorable outcome after ICI therapy in PD-L1-high NSCLC.

Tissue-specific thresholds of mutation burden associated with anti-PD-1/L1 therapy benefit and prognosis in microsatellite-stable cancers.

Immune checkpoint inhibitors (ICIs) targeting programmed cell death protein 1 or its ligand (PD-1/L1) have expanded the treatment landscape against cancers but are effective in only a subset of patients. Tumor mutation burden (TMB) is postulated to be a generic determinant of ICI-dependent tumor rejection. Here we describe the association between TMB and survival outcomes among microsatellite-stable cancers in a real-world clinicogenomic cohort consisting of 70,698 patients distributed across 27 histologies. TMB was associated with survival benefit or detriment depending on tissue and treatment context, with eight cancer types demonstrating a specific association between TMB and improved outcomes upon treatment with anti-PD-1/L1 therapies. Survival benefits were noted over a broad range of TMB cutoffs across cancer types, and a dose-dependent relationship between TMB and outcomes was observed in a subset of cancers. These results have implications for the use of cancer-agnostic and universal TMB cutoffs to guide the use of anti-PD-1/L1 therapies, and they underline the importance of tissue context in the development of ICI biomarkers.

Abstract 7621: Serum albumin and derived neutrophil-to-lymphocyte ratio are potential predictive biomarkers for immune checkpoint inhibitors in small cell lung cancer

Abstract Background: Immune checkpoint inhibitors (ICIs) have reshaped the treatment landscape of small cell lung cancer (SCLC), but only a minority of patients benefit from this therapy. Therefore, it is critical to identify potential risk factors that could predict the efficacy of ICI treatment in SCLC patients and identify patient subgroups who may benefit the most from ICI therapy. Methods: Our study included a total of 183 SCLC patients who had received at least one dose of ICI treatment. We utilized both logistic regression and Cox proportional hazard regression to evaluate whether various patient clinical factors and serum biomarkers, could serve as predictors of patient response to treatment and overall survival (OS) during ICI therapy. Results: Logistic regression showed that patients with a history of surgery (p=0.003, OR 9.06, 95% CI: (2.17, 37.9)) and no metastasis (p=0.008, OR 7.82, 95% CI: (1.73, 35.4)) exhibited a higher odds of response to ICI treatment. Cox regression analyses demonstrated that pretreatment blood albumin (p=0.003, HR 1.72, 95% CI: (1.21, 2.45)) and derived neutrophil to lymphocyte ratio (dNLR) (p=0.003, HR 1.71, 95% CI: (1.20-2.44)) were independent predictors for OS in SCLC patients. By establishing a pre-treatment prognostic scoring system based on baseline albumin and dNLR, we found that patients with high albumin and low dNLR exhibited a significantly better prognosis than those with low albumin and high dNLR in both the full (P<.0001, HR 0.33, 95% CI: 0.20-0.55) and the metastatic cohort (P<.0001, HR 0.28, 95% CI: 0.15-0.51). The better prognostic group also had younger age, higher BMI and lower systemic inflammatory biomarker values than the unfavorable group (P<.0001). Conclusion: Our data reveals the significant role of metastasis status and treatment history in predicting the initial response of SCLC patients to ICI treatment. However, baseline serum albumin and dNLR provide a more precise prognostic prediction for patient OS. The scoring system based on albumin and dNLR enhances the ability to stratify patient prognosis and holds the potential to guide clinical decision-making for SCLC patients undergoing ICI therapy. Citation Format: Zhanpeng Kuang, Jessica Miao, Xiaoli Zhang. Serum albumin and derived neutrophil-to-lymphocyte ratio are potential predictive biomarkers for immune checkpoint inhibitors in small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7621.

Abstract 5149: Extracellular matrix remodeling in metastatic mismatch repair deficient endometrial cancer:Implications for immune checkpoint inhibitor response prediction

Abstract Mismatch repair deficient (MMRd) status is a predictive biomarker for Immune checkpoint inhibitors (ICI) in endometrial cancer (EC), however, half of these patients (pts) do not respond. Most studies exploring biomarkers of response to ICI have focused on tumor or immune cell factors. We aimed to describe the extracellular matrix components of the tumor microenvironment (TME) in ICI-Responder (R) versus Non-Responder (NR) MMRd EC pts to identify new predictive biomarkers of response. Clinical data and outcomes of metastatic MMRd EC pts, treated with ICI (2016-2021), were retrospectively collected. Pts were classified as Rs (CR, PR, or SD ≥12 months) or NRs (PD or SD <12 months). Pre-ICI FFPE tumor samples were subjected to Biognosys UltraDeep TrueDiscovery™ Mass Spectrometry (MS) for identification of differentially regulated protein expression between R and NR. Criteria for protein candidate selection were p-value < 0.01 and average absolute log2 fold change (AVG Log ratio) > 0.58. Collagen was visualized on whole slides using Masson’s trichrome and quantified by Qupath. Collagen density was expressed as % positive surface in the intratumoral area. Second-harmonic generation (SHG) microscopy plus polarimetry (p-SHG) was used to estimate collagen content and describe the spatial orientation of fibrillar collagen in the intratumoral area. intraepithelial (ie) and stromal (s) CD3+ and CD8+ cells were quantified by Qupath. Non-parametric t-tests and Spearman’s rank coefficient (r) for linear correlation were used. Twenty-five tumor samples were included in the analysis: 17 from Rs and 8 from NRs. MS identified collagen type V alpha-2 (AVR Log ratio 2.9, p 0.008) and type XXII alpha-1 chains (AVR Log ratio 1.14, p 0.006) as significantly upregulated in NRs. Using spatial imaging, collagen density in the intratumoral area was significantly higher in NRs (median: 14.2% vs 4.6%, p 0.01). Intratumoral collagen density was positively correlated with collagen type V expression (r 0,54, p 0.016), and negatively correlated with ie and s CD3+ cell (r -0.39, p 0.054; r -0.4, p 0.048, respectively) and ie and s CD8+ cell (r -0.39, p 0.053; and r -0.29, p 0.166) infiltration. SHG confirmed that fibrillar collagen content in the tumor area was significantly greater in NRs (p 0.02). p-SHG revealed that NR tumors tended to show a highly disorganized collagen matrix. In contrast, a linear collagen pattern was associated with response to ICI: 89% of tumors displaying this pattern were Rs. Both MS and two different spatial approaches consistently demonstrated that increased collagen expression or density may serve as a potential predictive biomarker of resistance to ICI in MMRd metastatic EC, contributing to create an immunosuppressive TME. The spatial orientation pattern of collagen fibers may also be crucial in shaping immune TME and influencing the response to ICI. Citation Format: Juan Francisco Grau, Carole Aimé, Martin Mehnert, Elisa Yaniz-Galende, Catherine Genestie, Audrey Le Formal, Elodie Edmond, Antoine Amaury Lachaud, Patricia Pautier, Judith Michels, Sébastien Gouy, Amandine Maulard, Emeline Colomba-Blameble, Felix Blanc-Durand, Marie-Claire Schanne-Klein, Alexandra Leary. Extracellular matrix remodeling in metastatic mismatch repair deficient endometrial cancer:Implications for immune checkpoint inhibitor response prediction [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5149.

Abstract 7515: Enhancing immune checkpoint inhibitor efficacy with fulvestrant in estrogen receptor-positive breast cancer

Abstract Introduction: Breast cancer (BC) recurs decades after initial treatment that consists majority of the annual 43,000 BC deaths. Thus, Immune Checkpoint Inhibitor (ICI) therapy that bolster anti-cancer immunity is expected to improve long-term survival with reduced recurrence. Neoadjuvant ICI revolutionized management of triple negative breast cancer (TNBC); however, this represents only 5-7% of all BC cases, where estrogen receptor (ER)-positive subtype that consists of 70% of all BCs is not indicated due to less tumor-infiltrating lymphocytes (TILs). Using I-SPY2 trial we aim to investigate the potency of ER-alpha gene (ESR1) expression as a predictive biomarker, and whether the inhibition of the ER with fulvestrant enhances the efficacy of ICIs in ER+ BC. Methods:Total of 1157 BC patients from two independent cohorts (ISPY2 trial; n= 73, TCGA; n = 1084) were included, encompassing both clinical and transcriptomic profiles. The TIL score was determined using the xCell algorithm. Results:Using the transcriptome of the ISPY2 trial, we found that compared to ESR1 low expression patients, ESR1 high patients were associated with significantly lower pCR rates after neoadjuvant immunotherapy with ICI in whole cohort (n=71, pCR rate=30%, p<0.05) and HR+ subtype (n=50, pCR rate=20%, p<0.001), but not in triple-negative breast cancer (TNBC). ESR1 expression outperformed PD-1, PD-L1, and CTLA4 in Area Under the Curve (AUC) of the whole ISPY2 cohort (AUC=0.75, 0.68, 0.48, and 0.62, respectively), and further pronounced in HR+ BC (AUC=0.88, 0.73, 0.55, and 0.65, respectively), suggesting the potency of ESR1 expression as a predictive biomarker for ICI in HR+ BC. In agreement, ESR1 expression inversely correlated with the amount of intratumoral TILs consistently in both ISPY2 and TCGA cohorts in HR+ BC, but only in TCGA in whole cohort (all p<0.05). Among the intratumoral TILs, CD8+ T cell and M1 Macrophages were found to be less infiltrated in HR+ BC in TCGA. Given that ESR1 expression was associated with less intratumoral TILs and a poor response to ICI, we hypothesized that suppression of ER-alpha would enhance the effectiveness of ICI in HR+ BC in vitro. ER-alpha positive MCF7 cells were incubated with activated peripheral blood mononuclear cells with 1:1 ratio, and treated with 0.1 microgram of anti-PDL1, and 1nM of ER antagonist, fulvestrant, which demonstrated minimum cell killing. We found that ICI therapy with anti-PDL1 significantly decreased the cell viability of the MCF7 cells when ER-alpha expression was suppressed by fulvestrant, while activated peripheral blood mononuclear cells or anti-PDL1 alone or the combination did not exhibit any significant cell killing. Conclusion: We found that ESR1 expression is a predictive biomarker of ICI, and ER antagonist fulvestrant enhances the response of HR+ BC to ICI, suggesting that this combination could expand ICI indications to HR+ BC. Citation Format: Jun Arima, Kohei Chida, Masanori Oshi, Arya Mariam Roy, Kohei Taniguchi, Sang-Woong Lee, Kazuaki Takabe. Enhancing immune checkpoint inhibitor efficacy with fulvestrant in estrogen receptor-positive breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7515.

Abstract 1158: Spatially resolved cell profiling unveils tumor metabolic states associated with immunotherapy response in NSCLC

Abstract Background. Only a subset of non-small cell lung cancer (NSCLC) patients benefit from immune checkpoint inhibitors (ICIs). Thus, there is a clinical need to develop predictive biomarkers for ICIs. Deeper insights from the tumor microenvironment (TME) can lead to identification of spatial features associated with clinical responses to immune checkpoint inhibitors (ICI). In this study, we investigated functional profiles within cell subtypes as a surrogate for ICI clinical endpoints. Methods. We profiled a retrospective cohort of 39 NSCLC tissue cores from 27 patients treated with ICI, using highly multiplexed immunofluorescence (mIF) stained by the Phenocycler Fusion platform (Akoya Biosciences) capturing 45 proteins. Utilizing a deep learning based multiplex imaging analysis pipeline, cells were classified to 15 cell types by known marker expression and were further subclassified by unsupervised clustering. Cells were assigned to the tumor area or TME and more than 1000 spatial features were calculated based on cell type, marker positivity, and area assignments, and were compared between responders and non-responders to ICI therapy using Fisher’s exact and logrank tests. Results. Unsupervised cell subtyping of the 15 cell types identified 43 cell subsets, which were mostly segregated by their metabolism and activation status. Interestingly, all lymphocytes showed a similar pattern of clustering resulting in two clusters of metabolically active and inactive cells. The most significantly differentially expressed proteins between these cell types were oxidative phosphorylation proteins such as CS, SDHA and ATPA5, and other metabolic enzymes such as HK1, GLUT1 and LDHA. We found a direct connection between metabolic state, effector functions and tissue localization as the metabolically active lymphocytes exhibited higher levels of PD-1, MHC class I and II and CD44 positivity, and were more abundant within tumor infiltrating lymphocytes (TILs) and tertiary lymphoid structures (TLS). Unsupervised clustering of tumor cells demonstrated segregation to three main metabolic states - OXPHOS+, OXPHOS- and a third cluster (PPP+) which was characterized by upregulation of ASCT2, a glutamine transporter, as well as pNRF2 and G6PD, regulators of the pentose phosphate pathway. These cells also exhibited higher proliferation rate and CD44, a tumor stemness marker, positivity. All tumors with high content of PPP+ tumor cells (>40%) were resistant to PD-1 blockade (0/8 vs. 10/18 response rate in other tumors, p=0.009) and showed reduced overall survival (OS) rates (median OS of 27.6 vs 90.3 months, p=0.02). Conclusions. Taken together, this study reveals connections between metabolic states, effector functions, and immunotherapy outcome and contributes to the evolving landscape of predictive biomarkers for ICI therapies. Citation Format: James Monkman, Rotem Czertok, Shai Bookstein, Becky Arbiv, Yuval Shachaf, Ron Elran, Kenneth Bloom, Oscar Puig, Ken O'Byrne, Ettai Markovits, Arutha Kulasinghe. Spatially resolved cell profiling unveils tumor metabolic states associated with immunotherapy response in NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1158.

Abstract 7624: DNA checkpoint gene mutation as a biomarker of immune checkpoint inhibitor in advanced biliary tract cancer

Abstract Introduction: The DNA checkpoint (DNACHK) pathway is engaged in signaling the need for cell cycle arrest. The G1 and S phase checkpoint allows for repair of damaged DNA, preventing damaged DNA from being copied. The G2 and M phase checkpoint prevents transmission of mutated DNA to the next generation. This pathway, along with mismatch repair (MMR), homologous recombination (HR), and base excision repair (BER), is being actively researched to assess its role in cancer immunotherapy. Methods: Sixty-two patients participated in this study. These patients were treated with immune checkpoint inhibitors (ICIs) for advanced biliary tract cancers (BTCs) from Mar. 2020 to Aug. 2022 at Samsung Medical Center. DNACHK mutations were defined as genomic alterations such as SNVs, MNVs, and short insertion and deletions in seven genes These genes include checkpoint kinase 1 (CHEK1), checkpoint kinase 2 (CHEK2), BRCA1, DNA repair associated (BRCA1), the serine/threonine kinase ATM, the serine/threonine kinase ATR, and mediator of DNA damage checkpoint 1 (MDC1). We analyzed the effect of DNACHK mutations on the efficacy of ICIs in advanced BTCs. Results: Patient median age at diagnosis was 68.0 years. Ten patients (16.1%) had gall bladder (GB) cancer; the remaining patients (n = 52, 83.9%) were diagnosed with cholangiocarcinoma. Among the 62 patients with advanced BTCs treated with ICIs, 37 (59.7%) were categorized into the DNACHK wild-type (WT) group and 25 (40.3%) into the DNACHK mutated (MT) group. The most observed DNA checkpoint mutations were ATM mutations (n=14). MDC1 mutations were found in seven patients, ATR mutations in three, BRCA1 mutations in four, and CHEK2 mutations in three. Patients in the DNACHK MT group had better disease control rates than patients in the DNACHK WT group (60.0% vs. 48.6%, p=0.53). Median overall survival (OS) was 8.1 months (95% CI, 5.1, 22.8) in the MT group and 5.6 months (95% CI, 3.1, 11.0) in the WT group (p=0.33). Conclusions: The results of this study suggest that the DNACHK pathway may be a valuable source of biomarkers for ICI and worthy of further study. Citation Format: Ji Eun Shin, Seung Tae Kim, Dae-Ho Choi, Junho Lee, Jiyeon Hyeon. DNA checkpoint gene mutation as a biomarker of immune checkpoint inhibitor in advanced biliary tract cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7624.

Abstract 1213: Tissue-specific thresholds and microenvironment correlates of tumor mutation burden associated with immunotherapy benefit and prognosis in microsatellite stable cancers

Abstract Background: Immune checkpoint inhibitors (ICIs) targeting anti-PD-1/L1 have expanded the treatment landscape against cancers, but are only effective in a subset of patients across all cancer types. Tumor mutation burden (TMB) is postulated to be a generic determinant of ICI dependent-tumor rejection. Here, we clarify the association between TMB and survival outcomes among microsatellite-stable cancers in a real-world clinicogenomic cohort including 70,698 patients distributed across 27 histologies. Methods: Patients were segregated into mutually exclusive anti-PD-1/L1 (N=14,736, immune checkpoint inhibitor, ICI) and non-ICI cohorts (N=55,962) if they had received pembrolizumab, nivolumab, atezolizumab, durvalumab, avelumab, or cemiplimab, and non-ICI therapies, respectively, during the course of treatment for individual cancer types. Patients treated with chemo-immunotherapy combination regimens were included in the ICI cohorts, but anti-CTLA-4 agents were excluded from both cohorts. For both ICI and non-ICI cohorts, patients were reiteratively categorized as TMB-high or -low using increasing TMB thresholds up to the 90th percentile TMB for individual cancer types. Outcomes were then assessed using Cox regression analyses of overall survival (OS). Results: Across 27 histologies, 12 cancer types had at least one TMB cutoff associated with survival benefit upon ICIs (melanoma, NSCLC, SCLC, bladder, cervical, colorectal, gastric, ovarian, head and neck, vulvar cancers, as well as carcinoma of unknown primary, and sarcoma), and these associations were generally conserved across sex and age groups, although not necessarily significant in all cases. In two cancer types (cholangiocarcinoma and neuroendocrine tumors), TMB cutoffs were associated with worse OS with ICIs. The lowest TMB cutoff in which a survival benefit could be detected with ICIs ranged from 2 mut/Mb in melanoma to 9 mut/Mb in colorectal cancer. TMB thresholds with the greatest predictive value (defined as the lowest survival hazard ratio) were frequently near the highest TMB examined for individual cancer types, suggesting that TMB may scale with ICI benefit. Conclusion: TMB was associated with survival benefit or detriment depending on tissue and treatment context. Detectable survival benefits were noted over a broad range of TMB cutoffs across cancer types, and a dose-dependent relationship between TMB and outcomes was observed in a subset of cancers. These results may have implications for cancer-agnostic and universal TMB cutoffs to guide the use of anti-PD-1/L1 therapies, and underline the importance of tissue context in the clinical development of ICI biomarkers. Citation Format: Maishara Muquith, Magdalena Espinoza, Andrew Elliott, Joanne Xiu, Andreas Seeber, Wafik El-Deiry, Emmanuel S. Antonarakis, Stephanie Graff, Michael J. Hall, Hossein Borghaei, Dave S. Hoon, Stephen V. Liu, Patrick C. Ma, Rana R. McKay, Trisha Wise-Draper, John Marshall, George W. Sledge, David Spetzler, Hao Zhu, David Hsieh. Tissue-specific thresholds and microenvironment correlates of tumor mutation burden associated with immunotherapy benefit and prognosis in microsatellite stable cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1213.

Anti-integrin αvβ6 autoantibodies are a potential biomarker for ulcerative colitis-like immune checkpoint inhibitor-induced colitis

BackgroundNo specific biomarker for immune checkpoint inhibitor (ICI)-induced colitis has been established. Previously, we identified anti-integrin αvβ6 autoantibodies in >90% of patients with ulcerative colitis (UC). Given that a subset of ICI-induced colitis is similar to UC, we aimed to clarify the relationship between such autoantibodies and ICI-induced colitis.MethodsSerum anti-integrin αvβ6 autoantibody levels were compared between 26 patients with ICI-induced colitis and 157 controls. Endoscopic images of ICI-induced colitis were centrally reviewed. Characteristics of anti-integrin αvβ6 autoantibodies in the ICI-induced colitis patients were compared with those of UC patients.ResultsAnti-integrin αvβ6 autoantibodies were found in 8/26 (30.8%) patients with ICI-induced colitis and 3/157 (1.9%) controls (P < 0.001). Patients with anti-integrin αvβ6 autoantibodies had significantly more typical UC endoscopic features than those without the autoantibodies (P < 0.001). Anti-integrin αvβ6 autoantibodies in ICI-induced colitis patients were associated with grade ≥3 colitis (P = 0.001) and steroid resistance (P = 0.005). Anti-integrin αvβ6 autoantibody titers correlated with ICI-induced colitis disease activity. Anti-integrin αvβ6 autoantibodies of ICI-induced colitis exhibited similar characteristics to those of UC.ConclusionsAnti-integrin αvβ6 autoantibodies may serve as potential biomarkers for the diagnosis, classification, risk management, and monitoring the disease activity, of ICI-induced colitis.

PTCH1 mutation as a potential predictive biomarker for immune checkpoint inhibitors in gastrointestinal cancer.

Immune checkpoint inhibitors (ICIs) have become prominent therapies for gastrointestinal cancer (GC). However, it is urgent to screen patients who can benefit from ICIs. Protein patched homolog 1 (PTCH1) is a frequently altered gene in GC. We attempt to explore the association between PTCH1 mutation and immunotherapy efficacy. The MSKCC cohort (n = 236) with GC (esophageal, gastric and colorectal cancers) patients receiving ICIs was used for discovery and the Peking University Cancer Hospital (PUCH) GC cohort (n = 92) was used for validation. Overall survival (OS) and tumor mutational burden (TMB) of the PTCH1 mutant-type (PTCH1-MUT) and PTCH1 wild-type (PTCH1-WT) groups were compared. Furthermore, GC data were collected from TCGA to assess the potential mechanisms. In the MSKCC cohort, PTCH1-MUT group showed significantly better OS (P = 0.017) and higher TMB. Multivariate analysis showed that PTCH1 mutation was associated with better OS. In the PUCH cohort, PTCH1-MUT group showed significantly longer OS (P = 0.036) and PFS, and higher DCB and TMB. Immune cell infiltration analysis revealed that PTCH1-MUT group had significantly higher distributions of CD8 T cells, CD4 T cells, NK cells, mast cells, and M1 cells. The PTCH1-MUT group showed significantly higher expression of most immune- related genes. GSEA showed that the PTCH1-MUT group had enriched INF-γ response, INF-α response, glycolysis, and reactive oxygen species pathway gene sets. PTCH1 mutation may represent a potential biomarker for predicting ICIs response in GC. Nevertheless, prospective cohort studies should be performed to further validate our results.

The efficacy-associated biomarkers for immune checkpoint inhibitors in gastrointestinal cancer: a literature review.

Immune checkpoint inhibitors (ICIs) have been widely applied and studied in the treatment of gastrointestinal (GI) cancers, and have achieved good results. However, in clinical practice, it has been observed that only some patients respond well to ICIs, and some patients may experience various degrees of adverse reactions during the treatment. Timely evaluation of the potential therapeutic effects and adverse reactions of ICIs for patients has important clinical significance. This review aimed to summarize recent progress regarding efficacy-associated biomarkers for ICIs in GI cancer. The literature on ICI treatment in GI cancers was searched in the PubMed, Embase, and Cochrane Library databases for publications up to April 2023. Clinical practice and research has gradually revealed some biomarkers related to the treatment of GI cancers with ICIs, which can be roughly divided into three types: biomarkers that predict the effectiveness of ICIs treatment, biomarkers associated with resistance to ICIs, and biomarkers associated with immune related adverse events (irAEs). This review article provides a literature review on biomarkers related to the efficacy of ICIs in the treatment of GI cancers. According to existing clinical research results, there are multiple biomarkers that can be used for predicting and monitoring the efficacy and risk of adverse events of ICIs in the treatment of digestive system malignant tumors.

Nivolumab in patients (pts) with advanced gastrointestinal (GI) cancers with high plasma tumor mutational burden (pTMB): Results from a SCRUM-Japan GOZILA phase II trial.

98 Background: TMB is a biomarker for immune checkpoint inhibitors (ICIs). Analysis of circulating tumor DNA (ctDNA) has the potential to non-invasively identify pts likely to benefit from ICIs by assessing pTMB. We conducted a phase II basket trial as part of the SCRUM-Japan GOZILA umbrella/basket trial to evaluate the efficacy and safety of nivolumab monotherapy in pts with advanced GI cancers with high pTMB. Methods: Eligibility criteria included histologically confirmed unresectable or recurrent GI cancers; ECOG PS of 0 or 1; refractory or intolerant to the standard therapies; and high pTMB identified by Guardant360 CDx, a 74-gene ctDNA assay. Pts received intravenous nivolumab monotherapy of 360 mg every 3 weeks until progressive disease. The primary endpoint was objective response rate (ORR) per investigator assessment. The pTMB score was calculated by adjustment of mutation count by tumor fraction, and initial pTMB thresholds were determined based on previously reported ORR for ICI treatment for each GI cancer in the cohort. The cohort 2 proceeded only for esophageal cancer, and an ultra-high TMB cohort was created to include pts in the top 2% for pTMB scores. Results: Fifty-one pts with high pTMB in the cohort 1/2 (n=32) and the ultra-high TMB cohort (n=19) were enrolled. The median duration of follow-up was 7.5 months (range, 0.9–51.3). Deficient mismatch repair (dMMR) or high microsatellite instability (MSI-H) was observed in 1 pt in cohort 1/2 and 2 in ultra-high TMB cohort. The ORR was 12.5% and 21.1%, with median duration of response of 14.0 months and not reached, respectively. In an exploratory analysis of the overall population, pts with esophageal cancer had the highest ORR of 33.3% (4/12), followed by pancreatic (1/6, 16.7%) and colorectal cancer (3/27, 11.1%). Of 2 pts with proficient MMR/non-MSI-H colorectal cancer who had a response, 1 had a POLE mutation. Pts with response tended to have higher pTMB score (median, 26 vs. 8). dMMR/MSI-H (HR=0.16; 95% CI, 0.02–1.18), PD-L1 CPS ≥1 (HR=0.55; 95% CI, 0.29–1.01), and absence of liver metastasis (HR=0.36; 95% CI, 1.48–5.14) were significantly associated with longer progression-free survival. Treatment-related grade 3–4 adverse events occurred in 3 pts (9%) in the cohort 1/2 and 3 (16%) in the ultra-high TMB cohort, with no treatment death in either cohort. Conclusions: Nivolumab demonstrated antitumor activity in pretreated pts with advanced GI cancer and high pTMB. These results suggest that the use of pTMB potentially identify patients who may benefit from ICI treatment. Clinical trial information: UMIN000033182 .

Tissue biomarkers of immune checkpoint inhibitor therapy.

Cancer immunotherapy has been rejuvenated by the growing understanding of the immune system's role in tumor activity over the past two decades. During cancer initiation and progression, tumor cells employ various mechanisms that resemble peripheral immune tolerance to evade the antitumor responses of the immune system. Immune checkpoint molecules are the major mechanism of immune resistance that are exploited by tumor cells to inhibit T-cell activation and suppress immune responses. The targeting of immune checkpoint pathways has led to substantial improvements in survival rates in a number of solid cancers. However, a lack of understanding of the heterogeneity of the tumor microenvironment (TME) has resulted in inefficient therapy responses. A greater understanding of the TME is needed to identify patients likely to respond, and those that will have resistance to immune checkpoint inhibitors (ICIs). Advancement in spatial single-cell technologies has allowed deeper insight into the phenotypic and functional diversities of cells in the TME. In this review, we provide an overview of ICI biomarkers and highlight how high-dimensional spatially resolved, single-cell approaches provide deep molecular insights into the TME and allow for the discovery of biomarkers of clinical benefit.

An Exploratory Study of Early Immune Response Markers for Pembrolizumab in Urothelial Tract Cancer

Background: This prospective pilot study explored the potential of the innate immune system’s response to cancer-related immuno-stimulants as a predictive biomarker for Immune Checkpoint Inhibitor (ICI) effectiveness, using pembrolizumab-treated metastatic urothelial tract cancer (mUTC) patients as the study population. Methods: We included ten mUTC patients and assessed their innate immune responses before the first and second pembrolizumab cycles with the TruCulture® immunoassay. We also executed survival analysis and compared cytokine release. Results: R848-induced IFNα and HKCA-induced IL-10 values decreased in patients with disease progression (n = 7), while these values increased in non-progressing patients (n = 3), denoting a significant difference (p = 0.00192 and p = 0.00343, respectively). Further, an increased R848-induced IFNα response correlated with extended survival (log-rank p-value of 0.048). Conclusion: Our small study identified distinct immune response patterns following pembrolizumab’s first cycle in mUTC patients, hypothesizing the potential of an increased R848-induced IFNα response for improved survival outcomes. Further confirmatory studies are in progress.

A novel model for predicting prognosis and response to immunotherapy in nasopharyngeal carcinoma patients

Blood-based biomarkers of immune checkpoint inhibitors (ICIs) response in patients with nasopharyngeal carcinoma (NPC) are lacking, so it is necessary to identify biomarkers to select NPC patients who will benefit most or least from ICIs. The absolute values of lymphocyte subpopulations, biochemical indexes, and blood routine tests were determined before ICIs-based treatments in the training cohort (n = 130). Then, the least absolute shrinkage and selection operator (Lasso) Cox regression analysis was developed to construct a prediction model. The performances of the prediction model were compared to TNM stage, treatment, and Epstein–Barr virus (EBV) DNA using the concordance index (C-index). Progression-free survival (PFS) was estimated by Kaplan–Meier (K–M) survival curve. Other 63 patients were used for validation cohort. The novel model composed of histologic subtypes, CD19+ B cells, natural killer (NK) cells, regulatory T cells, red blood cells (RBC), AST/ALT ratio (SLR), apolipoprotein B (Apo B), and lactic dehydrogenase (LDH). The C-index of this model was 0.784 in the training cohort and 0.735 in the validation cohort. K–M survival curve showed patients with high-risk scores had shorter PFS compared to the low-risk groups. For predicting immune therapy responses, the receiver operating characteristic (ROC), decision curve analysis (DCA), net reclassifcation improvement index (NRI) and integrated discrimination improvement index (IDI) of this model showed better predictive ability compared to EBV DNA. In this study, we constructed a novel model for prognostic prediction and immunotherapeutic response prediction in NPC patients, which may provide clinical assistance in selecting those patients who are likely to gain long-lasting clinical benefits to anti-PD-1 therapy.

Multiplex analysis for the identification of plasma protein biomarkers for predicting lung cancer immunotherapy response.

Programmed death-ligand (PD-L1) expression serves as a predictive biomarker for immune checkpoint inhibitor (ICI) sensitivity in non-small cell lung cancer (NSCLC). Nevertheless, the development of biomarkers that reliably predict ICI response remains an ongoing endeavor due to imperfections in existing methodologies. ICIs have led to a new paradigm in the treatment of NSCLC. The current companion PD-L1 diagnostics are insufficient in predicting ICI response. Therefore, we sought whether the Olink platform could be applied to predict response to ICIs in NSCLC. We collected blood samples from patients with NSCLC before ICI treatment and retrospectively analyzed proteomes based on their response to ICI. Overall, 76 NSCLC patients' samples were analyzed. Proteomic plasma analysis was performed using the Olink platform. Intraplate reproducibility, validation, and statistical analyses using elastic net regression and generalized linear models with clinical parameters were evaluated. Intraplate coefficient of variation (CV) assays ranged from 3% to 6%, and the interplate CV was 14%. In addition, the Pearson correlation coefficient of the Olink Normalized Protein eXpression data was validated. No statistical differences were observed in the analyses of progressive disease and response to ICIs. Furthermore, no single proteome showed prognostic value in terms of progression-free survival. In this study, the proximity extension assay-based approach of the Olink panel could not predict the patient's response to ICIs. Our proteomic analysis failed to achieve predictive value in both response or progression to ICIs and progression-free survival (PFS).

Ultra-high combined positive score and high serum albumin are favorable prognostic biomarkers for immune checkpoint inhibitors in head and neck squamous cell carcinoma.

Biomarkers that predict response to immune checkpoint inhibitor (ICI) in recurrent metastatic squamous cell carcinoma of the head and neck (RMHNSCC) are not well known. We prospectively measured the combined positive score (CPS) and administered ICI to patients with RMHNSCC. Of 51 patients, 23 patients had a CPS <20 and 12 patients (23.5%) had a CPS ≥90. CPS showed a negative correlation with serum albumin. Survival analysis showed a 2-year survival rate of 24.1%. In multivariate analysis, CPS ≥90 (HR 0.3026, p = 0.02614) and albumin >3.5 (HR 0.3463, p = 0.01354) were the significant factors and plus chemotherapy (HR 0.4648, p = 0.07632) was not significant. Seven patients (14%) with CPS ≥90 and albumin >3.5 showed a 2-year survival rate of 66. 7%. CPS ≥90 and albumin >3.5 cases are a subgroup of RMHNSCC that respond extremely well to ICI.

Hepatocellular carcinoma immune prognosis score predicts the clinical outcomes of hepatocellular carcinoma patients receiving immune checkpoint inhibitors

ObjectiveThe predictive biomarkers of immune checkpoint inhibitors (ICIs) in hepatocellular carcinoma (HCC) still need to be further explored. This study aims to establish a new immune prognosis biomarker to predict the clinical outcomes of hepatocellular carcinoma patients receiving immune checkpoint inhibitors.MethodsThe subjects of this study were 151 HCC patients receiving ICIs at Harbin Medical University Cancer Hospital from January 2018 to December 2021. This study collected a wide range of blood parameters from patients before treatment and used Cox’s regression analysis to identify independent prognostic factors in blood parameters, as well as their β coefficient. The hepatocellular carcinoma immune prognosis score (HCIPS) was established through Lasso regression analysis and COX multivariate analysis. The cut-off value of HCIPS was calculated from the receiver operating characteristic (ROC) curve. Finally, the prognostic value of HCIPS was validated through survival analysis, stratified analyses, and nomograms.ResultsHCIPS was composed of albumin (ALB) and thrombin time (TT), with a cut-off value of 0.64. There were 56 patients with HCIPS < 0.64 and 95 patients with HCIPS ≥ 0.64, patients with low HCIPS were significantly related to shorter progression-free survival (PFS) (13.10 months vs. 1.63 months, P < 0.001) and overall survival (OS) (14.83 months vs. 25.43 months, P < 0.001). HCIPS has also been found to be an independent prognostic factor in this study. In addition, the stratified analysis found a significant correlation between low HCIPS and shorter OS in patients with tumor size ≥ 5 cm (P of interaction = 0.032). The C-index and 95% CI of the nomograms for PFS and OS were 0.730 (0.680–0.779) and 0.758 (0.711–0.804), respectively.ConclusionsAs a new score established based on HCC patients receiving ICIs, HCIPS was significantly correlated with clinical outcomes in patients with ICIs and might serve as a new biomarker to predict HCC patients who cloud benefit from ICIs.

Evaluating distinct KRAS subtypes as potential biomarkers for immune checkpoint inhibitor efficacy in lung adenocarcinoma.

Despite the acknowledged predictive value of KRAS in immune checkpoint inhibitor (ICI) responses, the heterogeneous behavior of its mutations in this sphere remains largely unexplored. As of now, no studies have definitively categorized KRAS subtype variations as independent prognostic indicators for ICI responses in lung cancer patients. We analyzed a cohort of 103 patients, all harboring different KRAS mutation subtypes, and complemented this data with information from TCGA and GEO databases. Our research focused on delineating the relationships between KRAS mutation subtypes and factors like immunotherapy markers and immune cell composition, in addition to examining survival rates, drug sensitivity, and PD-L1 responses corresponding to distinct KRAS subtypes. We found that the G12V and G12D subtypes demonstrated elevated expressions of immunotherapy markers, implying a potentially enhanced benefit from immunotherapy. Significant variations were identified in the distribution of naive B cells, activated CD4+ memory T cells, and regulatory T cells (Tregs) across different KRAS mutant subtypes. A notable difference was observed in the Tumor Mutation Burden (TMB) levels across the four KRAS subtypes, with the G12D subtype displaying the lowest TMB level. Furthermore, G12C subtype showcased the worst prognosis in terms of progression-free intervals (PFI), in stark contrast to the more favorable outcomes associated with the G12A subtype. Our study reveals that KRAS mutations exhibit considerable variability in predicting outcomes for LUAD patients undergoing ICI treatment. Thus, the evaluation of KRAS as a biomarker for ICIs necessitates recognizing the potential diversity inherent in KRAS mutations.