Outcomes Of Immune Checkpoint Inhibitors Research Articles

The prognostic impact of peripheral blood eosinophil counts in metastatic renal cell carcinoma patients treated with nivolumab

Although immune checkpoint inhibitors (ICIs) have gained approval for metastatic renal cell carcinoma (mRCC), the response rate is still limited. Therefore, it is urgent to explore novel markers of responses to ICIs that can help assess clinical benefits. Recently, it has been noted that peripheral blood eosinophil counts are an independent factor correlated with clinical outcome of ICIs in some types of cancer. We investigated peripheral blood absolute eosinophil counts (AECs) at baseline and 4 weeks after the initiation of nivolumab for mRCC patients between February 2016 and May 2022. In addition, we examined clinicopathological features including irAEs and analyzed the correlation between AECs and clinical efficacy of nivolumab. The median progression-free survival (PFS) and overall survival (OS) for all patients were 5.7 and 25.5 months, respectively. The median AECs in patients with irAEs were significantly higher at baseline and 4 weeks after the treatment compared to those without irAEs (p < 0.001 and p = 0.001). With the cutoff value of AECs of 329 cells/µL at 4 weeks after the treatment for prediction of irAEs, high-AECs groups had significantly higher number of responders compared with that in low-AECs group (p < 0.001). Accordingly, the PFS and OS were significantly better in patients with high-AECs group than those in low-AECs group (p = 0.03 and p = 0.009). High-AECs at 4 weeks after the treatment serve as the prominent surrogate marker associated with the incidence of irAEs and better clinical outcome in mRCC patients receiving nivolumab.

Clinical outcomes of immune checkpoint inhibitor combined with other targeted or immunological therapy regimens for the treatment of advanced bile tract cancer: a systematic review and meta-analysis

Clinical outcomes of immune checkpoint inhibitor combined with other targeted or immunological therapy regimens for the treatment of advanced bile tract cancer: a systematic review and meta-analysis

CT-derived skeletal muscle change before immunotherapy predicts survival of advanced gastric cancer: associations with inflammatory markers and liver lipid metabolism.

Skeletal muscle (SM) is a key factor in cancer treatment. However, it is unclear whether pretreatment SM change affects the outcome of immune checkpoint inhibitors (ICIs) therapy in gastric cancer (GC). Advanced GCs treated with ICIs were retrospectively investigated. SM evaluated by psoas muscle area at the third lumbar vertebra was measured on CT acquired within 1month from the start of ICIs therapy (CT-1), and on CT acquired 2.8 ± 0.84months before CT-1. Monthly change rate of SM (MCR-SM) was defined as the change rate of SMs between those two CTs divided by the period between those CTs (month). Monthly change rate of body weight (MCR-BW) during the same period was also calculated. They were compared with disease-specific survival (DSS) and progression-free survival (PFS). MCR-SM was compared with pretreatment markers including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), C-reactive protein (CRP), and liver-to-spleen CT attenuation ratio (LSR) as a marker of liver lipid metabolism. This study enrolled eighty-three GC patients. MCR-SM significantly correlated with DSS and PFS (P < 0.0001, 0.001, respectively), whereas MCR-BW did not. Kaplan-Meier analyses demonstrated that higher MCR-SM (MCR-SM ≥ -0.7185%) significantly associated with better DSS and PFS (P = 0.0002, 0.03, respectively). Patients with positive MCR-SM showed significantly lower NLR, MLR, and CRP than those with negative (P = 0.01, 0.006, 0.003, respectively). MCR-SM showed a significant positive correlation with LSR (P = 0.007, R = 0.30). Pretreatment SM loss, associated with high systemic inflammation and hepatic fat accumulation, related to poor outcome of ICIs therapy in GC.

Serum cytokines and creatinine/cystatin C ratio as prognostic biomarkers in advanced cancer patients treated with anti-PD-1/PD-L1 therapy.

Immune checkpoint inhibitors (ICIs), specifically targeting the programmed cell death protein-1 or its ligand (PD-1/PD-L1), have been extensively used in the treatment of a spectrum of malignancies, although the predictive biomarkers remain to be elucidated. This study aims to investigate the association between baseline circulating levels of cytokines and the creatinine/cystatin C ratio (CCR) with the treatment outcomes of ICIs in patients with advanced cancer. The pre-treatment circulating levels of 10 cytokines (PD-L1, CTLA4, CXCL10, LAG3, HGF, CCL2, MIG, GRANB, IL-18, and IL-6) were measured via automated capillary-based immunoassay platform in the serum of 65 advanced cancer patients treated with anti-PD-1/PD-L1-based systemic therapy and 10 healthy volunteers. The levels of cytokines and CCR were quantified and categorized into high and low groups based on the median value. The associations of serum cytokines and CCR with response to treatment, survival, and immune-related adverse events were assessed. Elevated circulating levels of 6 cytokines (PD-L1, CXCL10, HGF, CCL2, MIG, and IL-6) were observed in cancer patients compared with that in healthy volunteers. The correlation coefficients between cytokines, CCR and nutritional risk index were also calculated. In the cancer cohort (N = 65), low circulating HGF (P = 0.023, P = 0.029), low IL-6 (P = 0.002, P < 0.001), and high CCR (P = 0.031, P = 0.008) were associated with significantly improved progression-free survival (PFS) and overall survival (OS). Multi-variable COX analyses adjusted for clinicopathological factors revealed that low HGF, low IL-6, and high CCR were independent favorable prognostic factors for PFS (P = 0.028, P = 0.010, and P = 0.015, respectively) and OS (P = 0.043, P = 0.003, and P = 0.026, respectively). Grade 2 irAEs occurred more frequently in patients with low levels of circulating CCL2 and LAG3. Pre-treatment circulating levels of serum IL-6, HGF, and CCR may serve as independent predictive and prognostic biomarkers in advanced cancer patients treated with ICIs-based systemic therapy. These findings might help to identify potential patients who would benefit from these therapies.

PCDH11X mutation as a potential biomarker for immune checkpoint therapies in lung adenocarcinoma.

Immune checkpoint inhibitors (ICIs) have achieved impressive success in lung adenocarcinoma (LUAD). However, the response to ICIs varies among patients, and predictive biomarkers are urgently needed. PCDH11X is frequently mutated in LUAD, while its role in ICI treatment is unclear. In this study, we curated genomic and clinical data of 151 LUAD patients receiving ICIs from three independent cohorts. Relations between PCDH11X and treatment outcomes of ICIs were examined. A melanoma cohort collected from five published studies, a pan-cancer cohort, and non-ICI-treated TCGA-LUAD cohort were also examined to investigate whether PCDH11X mutation is a specific predictive biomarker for LUAD ICI treatment. Among the three ICI-treated LUAD cohorts, PCDH11X mutation (PCDH11X-MUT) was associated with better clinical response compared to wild-type PCDH11X (PCDH11X-WT). While in ICI-treated melanoma cohort, the pan-cancer cohort excluding LUAD, and the non-ICI-treated TCGA-LUAD cohort, no significant differences in overall survival (OS) were observed between the PCDH11X-MUT and PCDH11X-WT groups. PCDH11X mutation was associated with increased PD-L1 expression, tumor mutation burden (TMB), neoantigen load, DNA damage repair (DDR) mutations, and hot tumor microenvironment in TCGA-LUAD cohort. Our findings suggested that the PCDH11X mutation might serve as a specific biomarker to predict the efficacy of ICIs for LUAD patients. Considering the relatively small sample size of ICI-treated cohorts, future research with larger cohorts and prospective clinical trials will be essential for validating and further exploring the role of PCDH11X mutation in the context of immunotherapy outcomes in LUAD. KEY MESSAGES: PCDH11X mutation is associated with better clinical response compared to wild type PCDH11X in three ICIs-treated LUAD cohorts. In ICIs-treated melanoma cohort, the pan-cancer cohort excluding LUAD, and non-ICIs-treated TCGA-LUAD cohortsPCDH11X mutation is not associated with better clinical response, suggesting PCDH11X mutation might be a specific biomarker to predict the efficacy of ICIs treatment for LUAD patients. PCDH11X mutation is associated with increased PD-L1 expression, tumor mutation burden, and neoantigen load in TCGA-LUAD cohort. PCDH11X mutation is associated with hot tumor microenvironment in TCGA-LUAD cohort.

Does patient sex affect the treatment outcome of immune checkpoint inhibitors? A Danish, observational melanoma study

AimThe objective of this study was to evaluate whether patient biological sex influences treatment outcomes in patients with metastatic melanoma (MM) undergoing first-line immune checkpoint inhibitor (ICI) therapy. MethodsThe Danish Metastatic Melanoma Database (DAMMED) was employed to identify patients who underwent first-line ICI therapy for MM in Denmark from 2013 to 2021. Excluding adjuvant treatment, uveal and mucosal histological subtypes, the study conducted univariable and multivariable analyses to evaluate the influence of patient sex in survival analyses. Further, landmark survival of this real-world national cohort was described for progression free survival (PFS), overall survival (OS) and melanoma-specific survival (MSS). ResultsThe analysis encompassed a cohort of 1378 patients with MM. Compared to male sex, females had significantly improved OS (p = 0.003) when tested in univariable testing. Multivariable analyses, controlling for age, performance status, lactate dehydrogenase level, BRAF status, M-stage, and number of metastatic sites revealed significant favourable outcomes associated with female sex irrespective of the considered survival metrics (pPFS = 0.014, pOS = 0.002, and pMSS = 0.03). The observed five-year OS rates of the entire cohort were 47% and 38%, while melanoma-specific survival were 50% and 45% for female and male, respectively. ConclusionIn this nationwide cohort of patients with MM undergoing first-line ICI treatment females exhibited superior treatment outcomes compared to males. Sex was identified as an independent predictive variable for treatment outcomes, irrespective of the chosen outcome measures considered. Our analyses are not able to conclude whether the differences in outcome is attributable to differences in biology or to treatment strategy.

Diagnosis, management, and outcomes of immune checkpoint inhibitor induced acute interstitial nephritis: A single-center experience.

Immune checkpoint inhibitor (ICI)-associated acute interstitial nephritis (AIN) is a recognized complication of immunotherapy (IO), but literature on its management and outcomes is limited. We retrospectively reviewed patients who received ICIs and developed biopsy-proven or clinically-suspected ICI-associated AIN at the University of Virginia Comprehensive Cancer Center from 2012-2023. We analyzed baseline characteristics and clinical outcomes, including treatment interruption and rechallenge rates. Acute kidney injury (AKI) was defined as a ≥ 1.5-fold increase in baseline creatinine under seven days, a two-fold increase above the upper limit of normal, or an increase by ≥0.3 mg/dL. Kidney function returning to within 0.3 mg/dL or less than twice baseline was considered complete (CRc) and partial (PRc) recovery, respectively. We identified 12 cases of ICI-AIN: four by biopsy (33%) and eight (67%) by clinical suspicion. Two patients received anti-CTLA-4 and anti-PD1, six received anti-PD1 alone, and four received chemo-immunotherapy. The majority (58%) of patients developed AIN within the first 5 cycles. Eight patients developed ≥ Grade 3 AKI, and six developed multiple irAEs. ICI was permanently discontinued in seven patients (58%) and temporarily interrupted in four (30%). The CRc and PRc rates were 67% and 8%, respectively. Upon AIN onset, the best disease response was stable disease in five patients, partial response in three, and progressive disease in three. Median overall survival was 4.87 years, and progression-free survival was 1.5 years. Rechallenge with IO after kidney irAE may be possible in some patients but requires careful evaluation on an individual basis.

Association Between Serum Magnesium Levels and Outcomes of Atezolizumab in Patients With Metastatic Urothelial Carcinoma.

Evidence suggests that serum magnesium levels are associated with outcomes of immune checkpoint inhibitors (ICIs). However, this association remains under-explored in patients with metastatic urothelial carcinoma (UC) treated with ICIs. This prognostic study used individual participant-level data from 1,281 patients with locally advanced or metastatic UC treated with atezolizumab (N=855) or chemotherapy (N=426) who participated in the IMvigor210 and the IMvigor211 trials. Multivariable Cox proportional hazards regression and Fine-Gray subdistribution hazards regression models were used to examine the association of baseline serum magnesium levels with overall survival (OS), progression-free survival (PFS), and immune-related adverse events (irAEs). No evidence of an association was found between baseline serum magnesium levels and PFS or OS in patients treated with atezolizumab [PFS, hazard ratio (HR)=1.03, 95% confidence interval (CI)=0.78-1.35; OS, HR=1.13, 95%CI=0.84-1.51] or chemotherapy (PFS, HR=0.93, 95%CI=0.62-1.40; OS, HR=0.91, 95%CI=0.59-1.40). We also found no evidence of association with irAEs (subdistribution HR=1.29, 95%CI=0.81-2.07) in patients receiving atezolizumab. This study found no evidence of an association between baseline serum magnesium levels and treatment outcomes or irAEs in patients with metastatic UC receiving atezolizumab. Contrary to previous research suggesting a role for magnesium in cancer therapy, these results indicate that serum magnesium levels may not serve as a biomarker to predict outcomes in these patients.

Impact of concurrent medications on the outcome of immunotherapy in non-small cell lung carcinoma.

There have been reports on the impact of concurrent drugs on the outcome of immunotherapy for non-small cell lung carcinoma (NSCLC). However, the effect of some drugs, such as antibiotics and nonsteroidal anti-inflammatory drugs (NSAIDs), has not been clarified in patients with NSCLC. In the present study, we aimed to assess the association between concurrent drugs and the outcomes of immune checkpoint inhibitors (ICIs) alone or in combination with chemotherapy for patients with advanced NSCLC. We retrospectively assessed patients with advanced NSCLC who underwent ICI treatment between September 2017 and December 2021 at Kobe University Hospital. We evaluated the data regarding the use of antibiotics within 30 days before ICI initiation, as well as the use of proton pump inhibitors (PPIs) and NSAIDs during ICI initiation. A total of 127 patients were assessed, among whom 28 (22.0%) patients received antibiotics, 39 (30.7%) PPIs, and 36 (28.3%) NSAIDs. No significant differences were observed between the patients with and without antibiotic use. However, patients using NSAIDs had significantly worse objective response rates (ORR) and progression-free survival (PFS) with ICI alone or in combination with chemotherapy compared to those who did not (ORR, 47.2% vs. 67.0%; p = 0.045. PFS, 6.3 months vs. 10.8 months; p = 0.02). Patients using PPIs demonstrated a worse ORR of ICI in combination with chemotherapy compared to those who did not (ORR, 45.2% vs. 72.6%; p = 0.013). The unnecessary use of NSAIDs along with immunotherapy should be discouraged.

Abstract 5132: Multi-omics analysis uncovers predictive biomarkers for the efficacy and outcomes of immune checkpoint inhibitor in combination with chemotherapy in advanced unresectable biliary tract cancers

Abstract Background: Biliary tract cancer, typically diagnosed at advanced stages with a poor prognosis, has witnessed a glimmer of hope in the progress of immune checkpoint inhibitors (ICIs). Yet, their limited response rates necessitate the search for effective biomarkers to refine patient selection. Methods: A total of 125 patients with a confirmed histological diagnosis of unresectable advanced or metastatic biliary tract cancers (BTC) who received first-line ICIs in combination with chemotherapy (chemoimmunotherapy) were prospectively enrolled. All baseline samples from 125 patients underwent targeted DNA sequencing, with an additional 62 patients undergoing RNA sequencing, and 85 patients had accessible mIHC data. The associations between molecular characteristics and the response to chemoimmunotherapy, progression-free survival (PFS) and overall survival (OS) were evaluated. Results: The cohort had a median age of 63 years (range from 34 to 82) and 52.8% (66/125) were male, including 54 with gallbladder cancer, 57 with intrahepatic cholangiocarcinoma, and 14 with extrahepatic cholangiocarcinoma. The median duration of follow-up was 14.8 months for the entire cohort, with the median PFS and OS of 6.9 months (95%CI: 6.2-7.9) and 11.8 months (95%CI: 10.3-14.8), respectively. The most mutated genes were TP53 (64/125, 51.2%), KRAS (34/125, 27.2%), ERBB2 (18/125, 14.4%), and ARID1A (17/125, 13.6%). Mutations of TP53 (51.2%, p = 0.042), BRCA2 (4.8%, p = 0.002), cytokine genes (6.4%, p = 0.004), and high tumor mutation burden (p = 0.072) demonstrated significant correlation with chemoimmunotherapy response. KRAS G12D mutations (PFS: P &amp;lt; 0.001; OS: P = 0.034) and ARID1A loss-of-function mutations (PFS: P = 0.009; OS: P = 0.012) were adverse survival factors, while high CXCL9 or CTLA4 expression was associated with response (CXCL9, P = 0.014; CTLA4, P = 0.067), improved PFS (CXCL9, P = 0.018; CTLA4, P = 0.008), and longer OS (CXCL9, P = 0.010; CTLA4, P = 0.008) under chemoimmunotherapy. Patients were classified into three subtypes using the identified survival biomarkers. Among them, Type I patients, characterized by the absence of KRAS G12D or ARID1A mutations but expressing high levels of CTLA4 or CXCL9, demonstrated the best outcomes under chemoimmunotherapy. Interestingly, further RNA analysis suggested that elevated CXCL9 expression correlated with heightened immune checkpoint expressions, including CTLA4, PD-L1, and PD-1 (all P &amp;lt; 0.001), as well as increased tumor microenvironment immune activity, findings validated in two additional independent patient cohorts both internal and external. Conclusions: Our study revealed predictive biomarkers relevant to the response and efficacy of immune checkpoint inhibitors in combination with chemotherapy in advanced biliary tract cancer. Citation Format: Jieer Ying, Qi Xu, Jiaojiao Ni, Hanlin Chen, Chaoqun Li, Yanru Xie, Qinhong Zheng, Jianying Jin, Junrong Yan, Xiaoying Wu, Qiuxiang Ou, Li Yuan, Wei Zhuo, Haimeng Tang. Multi-omics analysis uncovers predictive biomarkers for the efficacy and outcomes of immune checkpoint inhibitor in combination with chemotherapy in advanced unresectable biliary tract 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 5132.

Abstract 4845: Evaluating racial disparities in immune checkpoint inhibitor survival and autoimmunity

Abstract Introduction: In recent years, immune checkpoint inhibitors (ICI) have revolutionized the landscape of treatment across a variety of cancers. Potential concerns regarding racial disparities in ICI access and therapeutic efficacy have been well documented. Recent studies have indicated improved ICI access and response outcomes in White patients compared to minority groups with head and neck cancer (HNC) and melanoma patients. In contrast, patients diagnosed with lung cancer have been mixed, with some research suggesting black patients may fare better with ICI therapy. Existing literature is largely limited to retrospective studies with small population sizes, and lacks comparisons of racial disparities across malignancies. We aim to describe and compare racial inequities in ICI outcomes in HNC, melanoma, and lung cancer. Methods: The TriNetX US Collaborative Network database was queried for patients &amp;gt;18 years-old with a diagnosis of head and neck cancer, melanoma or lung cancer that were treated with ICIs. Malignancy cohorts were defined by race: non-Hispanic White (NHW) and Black. Race cohorts were 1:1 propensity score matched (PSM) for comorbidities, oncologic stage, and chemoradiation treatment. Demographic differences in cohorts were evaluated prior to matching. Following PSM, overall survival and rates of autoimmunity were assessed at 5 years. Results: 19,443 NHW and 2,827 Black patients treated with ICI were identified. At a baseline, the Black patient cohorts had significantly higher rates of comorbidies (p&amp;lt;0.02). Across all malignancies, the geographic distribution of NHW patients was more equally distributed compared to Black patients (majority south). With PSM, black HNC patients had significantly lower survival rates compared to NHW [HR: 1.4 (1.2, 1.6), p=0.0002]. In melanoma, the same trend was present, though not significant [HR: 1.3 (0.95, 1.7), p=0.1]. In contrast, in lung cancer, Black patients had significantly higher survival rates compared to NHW patients [HR 0.78 (0.70, 0.86), p&amp;lt;0.0001]. In HN and lung cancer, NHW patients had significantly higher rates of autoimmune conditions after ICI therapy compared to Black [OR: 2.0 (1.4,2.8), 1.2 (1.0, 1.4), respectively]. Conclusion: This study represents the most extensive analysis of racial disparities on ICI outcomes across malignancies. This study found that black patients treated with ICIs had decreased survival rates at 5 years compared to NHW patients in HNC and melanoma, but increased survival rate in lung cancer. This disparity persisted following PSM, matching cohorts for comorbidities, oncologic stage and adjuvant therapy. Black patients also had significantly lower rates of autoimmunity in HN and lung cancer. Noted differences in survival may be a reflection of geographic practice differences, access to care and/or socioeconomic status. Further investigation is required to elucidate the underlying etiologies of these trends. Citation Format: Kathryn L. Nunes, Pablo Llerena, Praneet Kaki, Shreya Mandloi, Annie Moroco, Eric Mastrolonardo, David M. Cognetti, Adam J. Luginbuhl, Joseph M. Curry. Evaluating racial disparities in immune checkpoint inhibitor survival and autoimmunity [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 4845.

Abstract 4457: Skeletal muscle-infiltrating CD8 T cells exacerbate muscle atrophy in a syngeneic lung cancer cachexia mouse model

Abstract Cancer-associated cachexia (CAC) is a devastating syndrome of irreversible body weight loss and muscle wasting. CAC has been reported to often lead to poor outcomes of immune checkpoint inhibitors (ICIs), emerging as a standard treatment for various types of cancer. Previously, we have demonstrated that KRAS-mutant lung tumor tissues display an immunosuppressive microenvironment with decreased CD8 T cells and increased regulatory T cells (Tregs). In this orthotopic lung cancer mouse model, treatment with an anti-PD-L1 antibody, a representative ICI, reduced tumor burden, whereas accelerated loss of body weight and skeletal muscle mass. We thus assumed that CD8 T cells could facilitate skeletal muscle wasting in lung tumor-bearing mice, a key feature of CAC. First, we established a syngeneic CAC mouse model through orthotopic transplantation of murine lung cancer cells. At 7 weeks post-injection, these mice developed CAC, displaying over 20 % body weight loss, almost total loss of epididymal fats, and profound skeletal muscle wasting. In line with our assumption, CAC mice showed an increased number of CD8 T cells but a reduced number of Tregs in skeletal muscles, compared to tumor-free control mice. We then investigated whether skeletal muscle-infiltrating CD8 T cells directly induce muscle atrophy indeed. In CAC mice, CD8 neutralization led to restoration of muscle mass and downregulation of muscle atrophy markers, but was not able to significantly affect lung tumor burden. Moreover, direct co-culture with splenic CD8 T cells exacerbated C2C12 myotube atrophy in a conditioned medium from lung cancer cells, further supporting the involvement of CD8 T cells in CAC. To elucidate its underlying mechanism, RNA sequencing analysis was conducted in both skeletal muscles and lung tumors of CAC mice. Based on the differently expressed gene analysis, Cxcl13 was upregulated in skeletal muscles of CAC mice, while downregulated in lung tumors. It is well documented that CXCL13 can mediate recruitment of CD8 T cells. In this regard, CXCL13 might be a plausible regulator in CD8 T cell-induced skeletal muscle atrophy, which requires further investigation to fully understand the molecular mechanism. Citation Format: Se-Young Park, Bomi Kim, Myunggyo Lee, Haeseung Lee, Na-Young Song. Skeletal muscle-infiltrating CD8 T cells exacerbate muscle atrophy in a syngeneic lung cancer cachexia mouse model [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 4457.

Abstract 4967: Predicting progression-free survival (PFS) in first-line (1L) immune checkpoint inhibitor (ICI)-treated patients (pts) with advanced non-small cell lung cancer (aNSCLC): Machine learning (ML) application in real-world data

Abstract Introduction: Anti-programmed cell death (ligand)-1 ICIs are the standard of care 1L treatment for pts with aNSCLC without actionable oncogenic driver mutations. Heterogeneity in ICI utilization and outcomes is observed in real-world pts. By leveraging ML in electronic health records (EHRs), we identified predictors influencing key clinical outcomes, and developed a nomogram to predict likelihood of median PFS in 1L ICI-treated aNSCLC pts for potential risk stratification for interventions. Methods: 1L ICI-treated aNSCLC pts without ALK/ROS1/KRAS/BRAF/EGFR alterations were identified in a US oncology EHR database (ConcertAI; Jan 2015-Feb 2023). Survival ML models were trained on 112 clinical and demographic features with 5-fold nested cross-validation. The top predictors, determined by the best-performing ML model through SHapley Additive exPlanations and clinical judgement, were used to create a Cox proportional hazard (CPH) nomogram of median PFS. All models were evaluated using the concordance index (c-index). Patients were categorized as having high and low risk of progression/death at median PFS according to median risk predicted by the nomogram. Results: The study cohort had 4668 pts (median PFS: 6.1 months; 3811 events). The CPH nomogram predicting 6-month PFS had a c-index of 0.60 with the top 10 predictors identified using the XGBoost model (c-index: 0.62). Nomogram predictors included increased number of metastases, ECOG PS, cough suppressant use, WBC counts, and NLR (Table). Median probability of 6-month PFS for low- and high-risk groups was 35.9% and 19.4%, respectively. Conclusions: Future research should validate these findings and evaluate the opportunity to guide clinical practice to optimize outcomes in aNSCLC pts treated with 1L ICIs. Summary of top 10 clinical predictors at baseline Mean HR (95% CI) Max nomogram points Total metastases, n 1.15 (1.11-1.19) 100 ECOG PS, ordinal 1.14 (1.10-1.19) 55 Basophils, % 0.81 (0.73-0.90) 52 Albumin, g/dL 0.81 (0.75-0.87) 46 Chloride, mmol/L 0.98 (0.97-0.99) 46 Cough suppressants/expectorants, n 1.08 (1.03-1.14) 42 NLR 1.03 (1.02-1.05) 33 WBC counts, 103 cells/mL 1.02 (1.01-1.03) 29 PD-L1 expression, % 1.00 (1.00-1.00) 28 Presence of liver metastases 1.26 (1.15-1.39) 24 ECOG PS, Eastern Cooperative Oncology Group performance status; NLR, neutrophils-to-lymphocytes ratio; PD-L1, programmed cell death-ligand 1; WBC, white blood cell. Citation Format: Deep K. Hathi, James Harnett, Ning Wu, Zhenxing Xu, Weishen Pan, T G. Hager, Ruben G. Quek, Shivani Aggarwal, Young Kim, Petra Rietschel, Frank Seebach, Fei Wang, Ying Li. Predicting progression-free survival (PFS) in first-line (1L) immune checkpoint inhibitor (ICI)-treated patients (pts) with advanced non-small cell lung cancer (aNSCLC): Machine learning (ML) application in real-world data [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 4967.

Abstract 7618: Genomic pathogenic alterations of the SWI/SNF complex genes compromise the outcomes to immunotherapy in Chinese KRAS-mutant non-small cell lung cancer by downregulated STING

Abstract Background: Immune checkpoint inhibitors (ICIs) have been standard of care in non-small cell lung cancer (NSCLC), but lack of response to ICIs remains a major hurdle in cancer immunotherapy. Switch/sucrose nonfermentable (SWI/SNF) chromatin-remodeling complex mutations have been reported in KRAS-mutant cancers with debated influence to clinical outcome of ICIs, which needs further investigation. Methods: According to the OncoKB, COSMIC, and PolyPhen-2 databases, genomic pathogenic alterations (GPAs) of SWI/SNF are defined. Lung tumors were classified according to the presence or absence of mutations in six SWI/SNF genes (ARID1A, ARID1B, ARID2, PBRM1, SMARCA4, and SMARCB1). Lung cancer cell lines with different genotypes of SWI/SNF were used for differentially expressed genes analysis by RNA sequencing. Protein expression of STING was detected by immunohistochemistry (IHC) in tumor specimens. Results: Out of 2660 NSCLC patients (NSCLCs), the GPAs of SWI/SNF were detected in 15.0% (401/2660) patients. 23.1% (69/299) EGFRwtALKwt and 27.8% (25/90) STK11wtKEAP1wtKRASmut NSCLCs who received ICIs had SWI/SNF GPAs. Progression-free survival (mPFS) of SWI/SNF-wild type (wt) compared to SWI/SNF-mutant (mut) NSCLCs was not significantly different. However, GPAs of SWI/SNF in KRAS-mut ICI-treated NSCLCs associated with poorer clinical outcome. Patients with ARID1A, ARID1B, ARID2 or PBRM1 mutant tumors had a significantly shorter PFS (2.7 vs 6.5 months, HR=2.44 [95%CI: 1.31-4.54], P=0.004) as compared to SWI/SNF-wt patients. In STK11wtKEAP1wtKRASmut NSCLCs, all SWI/SNF mutations (4.9 vs 9.1 months, HR=2.03 [95%CI: 1.07-3.86], P=0.029) or ARID1A/ARID1B/ARID2/PBRM1 alterations (3.2 vs 9.1 months, HR=2.68 [95%CI: 1.33-5.41], P=0.004) significantly shortened the mPFS. In cell lines, SWI/SNF-mut cells had downregulated STING expression compared to SWI/SNF-wt cells. Downregulated STING protein were observed in KRAS-mut NSCLCs without benefit from the treatment of ICIs. Conclusions: In KRAS-mut NSCLCs with or without STK11/KEAP1 mutations, the presence of GPAs of DNA binding genes ARID1A/ARID1B/ARID2 could compromise the clinical outcome of immunotherapy, which might be due to the downregulated STING. Citation Format: Lingling Gao, Jie Jiang, Zhi Xie, Linlin Zhu, Yu Chen, Zhiyi Lv, Yuqing Chen, Wenbin Zhou, Ji Chen, Yumin Zhong, Li Zhang, Penghui Zeng, Xiaodan Huang, Wenqing Yan, Danxia Lu, Shuilian Zhang, Weibang Guo, Xuchao Zhang. Genomic pathogenic alterations of the SWI/SNF complex genes compromise the outcomes to immunotherapy in Chinese KRAS-mutant non-small cell lung cancer by downregulated STING [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 7618.

Abstract 912: CheckpointPx, an interpretable radiology AI tool, predicts checkpoint blockade benefit independent of PDL1 status in non-small cell lung cancers (NSCLC): A multi-institutional validation study

Abstract Background: Immune Checkpoint Inhibitors (ICIs) are a cornerstone in the treatment of cancers such as Non-Small Cell Lung Cancer (NSCLC). Despite the standard use of biomarkers such as PD-L1 expression for selecting ICI regimens, recent studies suggest missed opportunities for benefit in PD-L1 low/negative patients. Therefore, there is an urgent need for new biomarker strategies capable of guiding the use of ICIs in NSCLC. We introduce and validate an AI-powered radiology tool for ICI patient selection that provides interpretable predictions by quantifying aspects of tumor biology on baseline CT scans directly associated with ICI efficacy, such as tumor heterogeneity and twistedness of the tumor-associated vasculature. Methods: We analyzed CT scans of 439 patients treated with ICI at 4 institutions (D1-D4) using the Picture Health Px platform. Experienced radiologists and physicians across institutions delineated target lesions on baseline CT scans. A deep learning model was used to segment pulmonary vessels. CheckpointPx v1.11, an interpretable neural network incorporating quantitative features extracted from within the tumor and its vasculature, was trained to predict ICI response (defined as disease control per RECIST best overall response) on n=247 patients (D1-D3). It was assessed with respect to response and progression free-survival (PFS) on 192 patients (D2-D4), with D4 (n=105) being an external validation set. CheckpointPx was also evaluated within PDL1 subsets among testing set patients where available (n=138). Results: The cohort was predominantly late stage (Stage 3/4) (&amp;gt;85%) and was mixed with respect to ICI line of treatment (1st-4th). 122 of 247 (49%) and 119 of 192 (62%) were responders in training and test cohorts respectively. CheckpointPx included 16 features, such as entropy-based heterogeneity and quantitative vessel tortuosity (twistedness). The model predicted response to ICI with an AUC=0.65 on the test set. The CheckpointPx High Risk group significantly stratified patients by PFS (HR=1.67 [1.22-2.28], p=0.001). This separation remained significant within the subset of PDL1-negative (HR=2.71 [1.35-5.44], p=0.005) and PDL1-positive patients (HR=2.05 [1.22-3.46], p=0.007). Conclusions: From baseline radiology, CheckpointPx was shown to strongly predict ICI outcomes across multiple institutions, NSCLC stages, and lines of ICI. Furthermore, the tool stratified patients by ICI benefit within both PDL1-positive and negative subsets - suggesting the potential of CheckpointPx to address critical gaps in the NSCLC biomarker landscape. CheckpointPx is driven by interpretable imaging biomarkers, and thus its predictions are tied to specific and quantifiable phenotypic attributes of the tumor and its microenvironment. Citation Format: Amogh Hiremath, Seyoung Lee, Jeeyeon Lee, Peter Haseok Kim, Kai Zhang, Salie Lee, Monica Yadav, Maria Jose Aguilera Chuchuca, Taegyu Um, Myungwoo Nam, Liam Il-Young Chung, Hye Sung Kim, Jisang Yu, Trie Arni Djunadi, Leeseul Kim, Youjin Oh, Sungmi Yoon, Zunairah Shah, Yuchan Kim, Ilene Hong, Grace Kang, Jessica Jang, Amy Cho, Soowon Lee, Cecilia Nam, Timothy Hong, Yury S. Velichko, Amit Gupta, Vamsidhar Velcheti, Anant Madabhushi, Nathaniel Braman, Young Kwang Chae. CheckpointPx, an interpretable radiology AI tool, predicts checkpoint blockade benefit independent of PDL1 status in non-small cell lung cancers (NSCLC): A multi-institutional validation study [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 912.

Abstract 4170: Artificial intelligence (AI)-based multi-modal approach using H&amp;E and CT image for predicting treatment response of immune checkpoint inhibitor (ICI) in non-small cell lung cancer (NSCLC)

Abstract Background: Previously, AI-powered spatial tumor-infiltrating lymphocyte analysis in H&amp;E whole-slide image (WSI) showed promising performance in predicting ICI outcomes. However, there were several innate limitations of tissue analysis, including the time lag between tissue biopsy and actual ICI administration, during which tumor microenvironment (TME) has changed, and analyzing a part of a single tumor tissue would not fully assess immunogenicity of multiple metastatic tumors. To overcome the challenges, we developed multiple-instance learning (MIL)-based models and applied them to predict the treatment response of ICI in a real-world dataset. Method: MIL-based models were trained under the cross-validation scheme for CT scans (N=456) separately, based on CT image analyzers. Lunit SCOPE IO (Lunit, South Korea), an AI-based H&amp;E WSI analyzer, identifies various classes of cells within TME and segments tumor regions from WSI (AI-HE-TIL). An AI-based CT image analyzer detects nodules on the CT image (AI-CT). The final ensemble score per patient is computed by the average of all model predictions from CT and pathology image inputs. Single and ensemble performances for predicting responder and non-responder patients to ICI are measured in an independent cohort of 208 NSCLC patients. Results: In the overall cohort, the AUROC values for AI-HE-TIL, AI-CT, and the ensemble were 0.6372, 0.6759, and 0.7307, respectively. The high ensemble score group (≥ median) has prolonged progression-free survival (PFS) of ICI (median PFS 5.0 months vs 2.1 months, hazard ratio [HR] 0.54, P &amp;lt; 0.0001). It correlates with PD-L1 expression, as tumor proportion score (TPS) ≥ 50% subgroup had higher ensemble score (median 0.312 vs 0.257, P = 0.0295). Interestingly, among TPS ≥ 50% subgroup, the high ensemble score shows significantly favorable PFS of ICI (median PFS 6.7 months vs 2.9 months, HR 0.46, P = 0.0002). In subgroup analysis according to tissue harvest site (primary tumor vs lymph node or distant metastasis), the AUROC values of AI-HE-TIL and AI-CT for the subgroup harvested from the primary tumor (N=111) were 0.6568 and 0.6658, respectively, and those for the subgroup harvested from the metastatic lesion (N=97) were 0.6162 and 0.6973, respectively, implying AI-CT is relatively not affected by tissue harvest site. Conclusion: AI-powered multi-modal approach of using H&amp;E image and CT image shows complimentary, and synergistic effect to predict ICI clinical outcomes in advanced NSCLC, even in the subgroup of PD-L1 high population. Citation Format: Dong Young Jeong, Jongchan Park, Heon Song, Jimin Moon, Taebum Lee, Changho Ahn, Sehhoon Park, Se-Hoon Lee, Chan-Young Ock, Ho Yun Lee. Artificial intelligence (AI)-based multi-modal approach using H&amp;E and CT image for predicting treatment response of immune checkpoint inhibitor (ICI) in non-small cell lung cancer (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 4170.

Abstract A104: Losartan rewires ovarian cancer tumor-immune microenvironment and suppresses IGF-1 to amplify chemo-immunotherapy sensitivity

Abstract Background: Ovarian Cancer (OvCa) is the most lethal gynecologic malignancy worldwide. The use of immune checkpoint inhibitors (ICIs) has revolutionized the therapy of several malignancies. Unfortunately, ICIs have had limited efficacy in OvCa, with objective response rates in only 10 to 15% of patients. Prevailing preclinical and clinical data indicate that abnormalities in the tumor microenvironment (TME) contribute to immunosuppression and dictate the outcome of ICIs. OvCa harbors an abnormal TME, characterized by a desmoplastic extracellular matrix with high collagen levels. The accumulation of extracellular matrix components gives rise to increased compressive forces within the tumor, leading to blood vessel collapse and vessel perfusion reduction, causing impaired drug delivery and compromised trafficking of cytotoxic T-cells. The resulting TME is hypoxic and immunosuppressive. In our attempts to normalize the TME, we discovered that angiotensin II receptor 1 (AT1) is a key regulator of compressive solid stress. We showed in OvCa models that treatment with losartan – a widely prescribed anti-hypertensive drug – reduced matrix content and re-opened compressed vessels. As a result, blood perfusion increased, leading to enhanced drug delivery and improved chemotherapy efficacy. Furthermore, our retrospective analysis demonstrated that treatment with angiotensin blockers is associated with a 30-month overall survival benefit in OvCa patients. As a natural extension of this study, we are now asking the question: Can losartan reprogram the immunosuppressive TME of OvCa to enhance immunotherapy alone or with chemotherapy? Methods and Results: Here, using two syngeneic immunocompetent OvCa models and genetic and pharmacologic perturbations, we discovered that losartan – a widely prescribed anti-hypertensive drug – exhibits dual effects on both the TME and cancer cells to sensitize OvCa to chemo-immunotherapy. Specifically, losartan treatment i) reprograms the TME, leading to increased vascular perfusion, and thus enhances ICI drug delivery and immune effector cell intratumoral infiltration and function; and ii) rewires the OvCa cells by suppressing the IGF-1 signaling, resulting in enhanced chemosensitivity. As a result of the combined tumor and stromal effects, losartan treatment enhances the efficacy of chemo-immunotherapy in OvCa models. Conclusions: Two of the greatest problems in ovarian cancer are chemotherapy resistance and the failure of immunotherapeutics to successfully alter the course of patients with OvCa. Our study offers a novel combination treatment strategy that can potentially enhance chemo-immunotherapy efficacy. As one of the most prescribed drugs for hypertension, the safety and low cost (less than $1-2/day) of losartan warrants rapid translation of our research to patients with OvCa. Citation Format: Yao Sun, Zhenzhen Yin, Limeng Wu, Changli Yue, Sonu Subudhi, Pinji Lei, Alona Muzikansky, Bo R. Rueda, Lei Xu. Losartan rewires ovarian cancer tumor-immune microenvironment and suppresses IGF-1 to amplify chemo-immunotherapy sensitivity [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr A104.

Clinical variables associated with immune checkpoint inhibitor outcomes in patients with metastatic urothelial carcinoma: a multicentre retrospective cohort study

ObjectivesImmune checkpoint inhibitors (ICIs) are indicated for metastatic urothelial cancer (mUC), but predictive and prognostic factors are lacking. We investigated clinical variables associated with ICI outcomes.MethodsWe performed a multicentre retrospective...

DLGAP5 promotes lung adenocarcinoma growth via upregulating PLK1 and serves as a therapeutic target

BackgroundHuman discs large-associated protein 5 (DLGAP5) is reported to play a pivotal role in regulating the cell cycle and implicate in tumorigenesis and progression of various cancers. Our current research endeavored to explore the prognostic value, immune implication, biological function and targeting strategy of DLGAP5 in LUAD through approaches including bioinformatics, network pharmacology analysis and experimental study.MethodsMultiple databases, including TCGA, GEO, CPTAC and Human Protein Atlas, were utilized to explore the expression and clinical significance of DLGAP5 in LUAD. The genetic alterations of DLGAP5 were assessed through cBioPortal and COSMIC databases. The relationship between DLGAP5 expression and genetic abnormalities of driver genes in LUAD was analyzed through TIMER2.0 database. CancerSEA database was utilized to explore the function of DLGAP5 in 14 different states in LUAD at single-cell resolution. GDSC database was utilized to analyze the impact of DLGAP5 on IC50 of frequently-used anti-LUAD drugs. CIBERSORT method and TIMER2.0 database was utilized to explore the relationship between DLGAP5 and tumor immune infiltration. Network pharmacology was applied to screen potential DLGAP5 inhibitor. In vitro and in vivo experiments were utilized to evaluate biological function and downstream targets of DLGAP5, and the effect of screened DLGAP5 inhibitor on LUAD growth.ResultsHigh DLGAP5 expression was commonly observed in LUAD and associated with mutation of major driver genes, poor prognosis, high IC50 values of frequently-used anti-LUAD drugs, increasing immune infiltration and elevated immune checkpoint blockade-related genes in LUAD. PLK1 was revealed as a potential DLGAP5 downstream target in LUAD. DLGAP5 overexpression or knockdown significantly promoted or inhibited LUAD cell proliferation and PLK1 expression. PLK1 overexpression well rescued DLGAP5 knockdown-induced cell proliferation inhibition, or vice versa. Furthermore, by virtual screening of an investigational drug library from the DrugBank database, AT9283 was screened and identified as a novel DLGAP5 inhibitor. AT9283 effectively suppressed growth of LUAD cells both in vitro and in vivo. DLGAP5 overexpression significantly reversed AT9283-induced proliferation inhibition. Moreover, AT9283 significantly suppressed DLGAP5 and PLK1 expression, while DLGAP5 overexpression significantly reversed AT9283-induced PLK1 suppression.ConclusionOur research has demonstrated that DLGAP5 is upregulated in LUAD and exhibits a strong correlation with unfavorable prognosis. Furthermore, DLGAP5 assumes a significant function in the regulation of tumor immunity and treatment outcome of immune checkpoint inhibitors. Of note, we found that DLGAP5 promotes cell proliferation of LUAD via upregulating PLK1. Targeting DLGAP5 by AT9283, our newly identified DLGAP5 inhibitor, suppresses LUAD growth. DLGAP5 may become a promising prognostic biomarker and therapeutic target for patients with LUAD.

Effect of type of antibiotics (Abx) on outcomes with immune checkpoint inhibitors (ICIs) in patients (pts) with metastatic urothelial carcinoma (mUC) in a real-world setting.

640 Background: Use of Abx was associated with worse overall survival (OS) and progression-free survival (PFS) in our real-world cohort of mUC pts treated with ICI. (ASCO 2023). We now report the effect of type of Abx on ICI outcomes. Methods: In our cohort of 335 pts with mUC treated with ≥2 cycles of ICI with atezolizumab (A) or pembrolizumab (P) at CCF between 2015 and 2023, Abx class used in at least 20 pts was included. PFS and OS were calculated using Kaplan-Meier method, outcomes compared using log-rank testing and multivariate (MVA) Cox regression method. Results: Of 335 pts, 26.27% received A and 73.73% received P. Median follow-up was 26.8 mos. Details of type of Abx (cephalosporins (CPH), fluoroquinolones (FQ), penicillins (PCN) and trimethoprim-sulfamethoxazole (TMP-SMX), timing (30 or 60 (d) pre or post ICI start) and OS/PFS are shown in the Table. On MVA Cox regression analysis, Abx use within 60 (d) before ICI start was associated with worse OS (10.97 vs 16.03 mos.; (HR) 1.6 [1.2 -2.1], p=0.0004). Abx use within 30 (d) post ICI was associated with worse OS (6.9 vs 14.39 mos, p=0.008). Individual Abx and effect on OS and PFS are shown in Table. On MVA Cox regression analysis, Abx use within 60 (d) post ICI start was associated with worse PFS (3.12 vs 5.67 mos., HR 1.4; p=0.015). Conclusions: In our large cohort of pts with mUC treated with ICI, Abx PCN, CPH and FQ, within 30 and 60 (d) prior to starting ICIs demonstrated worse OS, Abx used after 30 and 60 (d) of ICI demonstrated worse OS and PFS, especially with CPH and PCN but not FQ. These findings have the potential to influence clinical practice, including using a higher threshold for prescribing antibiotics to pts with mUC when planned for or on ICI and the choice of Abx used. [Table: see text]