Immune Checkpoint Inhibitor Resistance Research Articles

Abstract 1247: Comprehensive molecular profiling to predict first-line immunochemotherapy outcomes in inoperable esophageal adenocarcinoma

Abstract For patients with inoperable esophageal adenocarcinoma (EAC), prognosis on conventional chemotherapy (CTX) remains poor. In 2021, the FDA approved two αPD-1 immune checkpoint inhibitors (ICI) for addition to fluoropyrimidine/platinum-containing CTX in this first-line setting. As ICI+CTX enters the clinic, understanding ICI responses and predicting which patients will benefit from ICI addition are key challenges. To address these challenges, we assessed clinical and molecular profiles from the experimental LUD2015-005 trial (NCT02735239, EudraCT 2015-005298-19). Treatment consisted of an initial four-week ICI-only window with durvalumab (αPD-L1) with or without a single dose of tremelimumab (αCTLA-4), followed by 6 cycles of ICI+CTX (CapOx). 38 inoperable patients received treatment (35 EAC; 3 ESCC); median overall survival (OS) and progression-free survival (PFS) were 13.4 and 9.3 months, respectively. All patients reported at least one treatment emergent adverse event (TEAE), with 29 (76.3%) reporting grade 3 or higher TEAEs. EAC patients with available samples (n = 33) were taken forward for biomarker analysis, using tumor and adjacent normal biopsies collected at pre-treatment (PreTx), after four weeks of ICI-only (ICI-4W), and at the end of ICI+CTX (PostTx). Transcriptomic comparison of paired PreTx and ICI-4W EAC biopsies (n = 28) revealed ICI-induced upregulation of a novel T-cell inflammation signature (termed INCITE). Stronger INCITE upregulation correlated with greater tumor shrinkage during the ICI-only window, and tumors with minimal INCITE upregulation showed markers of ICI resistance, including Innate PD-1 Resistance (IPRES). Despite correlation with ICI-only responses, INCITE changes were not associated with overall ICI+CTX outcomes. To find predictive biomarkers of ICI+CTX outcomes, we conducted comprehensive genomic and transcriptomic profiling of PreTx EAC biopsies (n = 33). First, we generated a novel 65,000 cell scRNA-seq dataset and designed a deconvolution workflow to resolve tumor cell composition. Unexpectedly, monocyte composition was strongly linked with greater overall survival (OS) (HR: 0.40 [0.23-0.69]; p = 0.001; FDR = 0.047). Coding tumor mutational burden (TMB) was also associated with improved OS (HR: 0.50 [0.28-0.89]; p = 0.019). Multivariate modelling suggested monocyte composition and TMB were independent and complementary predictors of outcomes. Neither factor was associated with outcomes in a TCGA cohort of EAC patients not treated with ICI, suggesting these biomarkers may be specific to ICI or ICI+CTX. Our findings suggest monocyte composition and TMB may identify EAC patients likely to benefit from ICI+CTX. INCITE upregulation may also serve as a useful monitor of ICI efficacy. These timely findings further our understanding of ICI response and resistance and may help inform patient selection for ICI+CTX. Citation Format: Thomas M. Carroll, Joseph A. Chadwick, Richard P. Owen, Michael J. White, Joseph Kaplinsky, Iliana Peneva, Anna Frangou, Jaeho Chang, Phil F. Xie, Andrew Roth, Bob Amess, Hantao Lou, Katy J. McCann, Georgina Berridge, Roman Fischer, Chansavath Phetsouphanh, Ayo O. Omiyale, Brittany-Amber Jacobs, David Ahern, Simon R. Lord, Stewart Norris-Bulpitt, Sam T. Dobbie, Lucinda Griffiths, Kristen Aufiero Ramirez, Toni Ricciardi, Mary J. Macri, Aileen Ryan, Ralph R. Venhaus, Benoit J. Van den Eynde, Ioannis Karydis, Benedikt M. Kessler, Benjamin Schuster-Böckler, Mark R. Middleton, Xin Lu. Comprehensive molecular profiling to predict first-line immunochemotherapy outcomes in inoperable esophageal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1247.

Abstract 2334: Inhibition of DHFR modulates anti-tumor immunity

Abstract Lung cancer is the second most common type of cancer in both men and women and has the highest mortality rate. Non-small cell lung cancer (NSCLC) makes up most cases. Immune checkpoint inhibitors have significantly improved the clinical management of some NSCLC cases, yet many lung cancer patients still fail to respond to conventional immunotherapy. Therefore, more research is needed to characterize cellular pathways contribute to immune checkpoint inhibitor (ICI) resistance in NSCLC patients. Dysregulated cellular metabolism is a common feature of many cancer types, and metabolites are now known to modulate several functions inside cells such as signaling pathways and epigenetic control of gene expression. Therefore, targeting tumor metabolism may be able to combat NSCLC immunotherapy resistance. To identify potential metabolic pathways involved in the anti-tumor immune response, we employed a metabolic inhibitor-based drug screen in human NSCLC cell lines and tested for expression changes in a panel of known immune regulator genes. Notably, pharmacologic inhibition of dihydrofolate reductase (DHFR) downregulated the mRNA expression of anti-phagocytic surface protein cluster of differentiation 24 (CD24) in lung cancer cells. In line with this, shRNA knockdown and overexpression of DHFR, decreased and increased CD24 RNA and protein levels, respectively. These results show that the metabolic enzyme DHFR is involved in CD24 gene expression. Cancer cells heavily rely on DHFR for enhanced nucleotide biosynthesis to facilitate rapid tumor growth, and DHFR inhibitors are already used in the clinic for cancer therapy. This study highlights a novel interaction between reprogrammed cancer metabolism and the anti-tumor immune response, with possible clinical implications for DHFR inhibitors such as methotrexate in combination with conventional cancer immunotherapy agents. Citation Format: Austin Boese, Isabelle Young, Jihoon Kang, Courteney Malin, Jung Seok Hwang, Sumin Kang. Inhibition of DHFR modulates anti-tumor immunity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2334.

Abstract 2027: Spatial omics and multiplexed imaging to discover new biomarkers of response or resistance to immune checkpoint inhibitors (ICI) in advanced non-small cell lung cancer (NSCLC)

Abstract Introduction: Despite the impressive outcomes with ICI in NSCLC, only a minority of the patients show long-term benefit from ICI. While PD-L1 immunohistochemistry is an approved companion diagnostic test, it is neither sensitive nor specific. Here, we describe the use of spatial transcriptomics using the GeoMx Digital Spatial Profiler (DSP) as a discovery platform to find biomarkers for ICI response or resistance. Methods: Pre-treatment samples from 56 patients with NSCLC treated with ICI were collected and analyzed in a tissue microarray (TMA) format in two-fold redundancy. The human whole transcriptome, represented by 18000 genes assessed by oligonucleotide-tagged in situ hybridization, was sequenced on the NovaSeq platform to quantify the mRNAs present in each region of interest. Three molecularly defined tissue compartments, defined by fluorescence co-localization (tumor [panCK+], leukocytes [CD45+/CD68-], macrophages [CD68+]) were generated to assess mRNA. All statistical testing was performed using a two-sided significance level of α=0.05. Result: 54000 gene variables were generated per case, from them about 27000 were analyzed after removing targets with expression lower than a prespecified frequency. Expression distribution of EPCAM in tumor, PTPRC in leukocytes and CD68 in macrophages confirmed that DSP successfully profiled the molecular compartments. Differential gene expression (DEG) analysis was performed for 6-month clinical benefit across two distinct tumor TMA spots per patient. This resulted in a DEG list of about 250, 125 and 122 genes in CK, CD45 and CD68 compartment respectively. When we used the intersection of significantly associated with benefit genes the candidate list was reduced dramatically to 5, 10 and 10 distinct genes in CK (CYBA, ESD, SH3BGRL3, TOP2B, UFM1), CD45 (ATRN, DGAT1, DNAAF9, GMPS, IFT20, MPHOSPH6, PKP4, SOCS2, TFAP4, TGFB3) and CD68 (ANKS3, ARFRP1, CTSD, DPYD, GTF3C5, HS2ST1, KIAA0895L, PIGR, SFTPA2, YEATS4) compartment respectively. From them, using the Cox Proportional-Hazards Model we further identified CYBA, ESD and UFM1 in CK, DGAT1 and IFT20 in CD45 and ANKS3 and DPYD in CD68 to predict survival as well. Conclusions: Using DSP technology allows rapid, patient-specific assessment of the transcriptome in TMAs by in situ hybridization in spatially defined molecular compartments. Here we show a small set of candidate genes that are associated with outcome in this ICI-treated cohort. By intersecting two non-adjacent cores of the same patient tissue sample, we have begun to dissect tumor heterogeneity and pilot biomarker candidate information with unique molecularly defined compartments for tumor cells, lymphocytes, and macrophages. Results from this cohort may lead to a novel, spatially defined, transcriptomic approach for developing new biomarkers for immunotherapy. Citation Format: Myrto Moutafi, Sandra Martinez-Morilla, Rolando Garcia-Milian, Thazin Nwe Aung, Ioannis Vathiotis, Niki Gavrielatou, Vasiliki Xirou, Leonidas Salichos, David L. Rimm. Spatial omics and multiplexed imaging to discover new biomarkers of response or resistance to immune checkpoint inhibitors (ICI) in advanced non-small cell lung cancer (NSCLC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2027.

Abstract 1258: Elevated serum DC-HIL is associated with poor response to immune checkpoint inhibitors (ICI) in metastatic renal cell carcinoma (mRCC)

Abstract ICI therapy has shown unprecedented clinical outcomes in mRCC patients, but durable responses have been limited by innate (never respond initially) and acquired resistance (initially respond but eventually develop cancer progression). Establishment of predictive biomarkers for response to ICI maximizes the therapeutic benefit. Since no such marker exists, we investigated DC-HIL/GPNMB as a possibility because we detected DC-HIL to be elevated in blood of patients with metastasis, as both a receptor on myeloid-derived suppressor cells (MDSC) and as a soluble form (sDC-HIL); and found DC-HIL to be relevant to ICI resistance in mice. We studied 27 mRCC patients treated with combination ICI (Ab to PD1/PDL1/CTLA4) and assessed tumor response (by RECIST) at 12 wk after therapy. Blood was collected before and after treatment and assayed by FACS for expression of DC-HIL and PDL1 on CD14+HLA-DRno/lo monocytic (mMDSC) and CD15+CD11b+ granulocytic MDSC (gMDSC). T-cell suppressor function was assayed by cell culture. We showed both MDSC subsets to express DC-HIL predominantly over PDL1. We also showed mMDSC to be more potent T-cell suppressors than gMDSC (85% vs. 58% suppression, p=0.012) and to also be more dependent on DC-HIL for such suppression (56% vs. 15% restoration of T-cell function after adding DC-HIL mAb, p=0.013). However, there was no significant difference in % DC-HIL+MDSC/PBMC between ICI responders and non-responders (p=0.15). We next examined the relationship between tumor response (at 12 wk) and blood sDC-HIL (by ELISA) in 31 mRCC patients. At baseline, non-responders (n=10) had a significantly higher sDC-HIL than responders (n=21) (14 ± 2.4 vs. 10 ± 4.6 ng/ml, p=0.004), but no difference in blood PDL1 or VEGF. Among initial responders (n=22), 50% maintained a positive response while the other half acquired resistance after 20 wk. Among initial non-responders (n=9), 77% never responded while 22% responded positively after 20 wk. We then analyzed changes over time in sDC-HIL levels after treatment (up to 60 wks) in individuals. Patients who responded positively to ICI at treatment inception and through 40 wk maintained blood sDC-HIL at levels lower than the median for all positive responders. Initial responders who acquired resistance (9 out of 11 patients) had low blood sDC-HIL that rose during cancer progression. All constant non-responders (n=7) had high blood sDC-HIL that remained high during the study. To our surprise, the 2 initial non-responders who responded positively after 20-40 wk of ICI displayed an abrupt rise in blood sDC-HIL during their positive response. Our results indicate blood sDC-HIL as a promising biomarker for prognosticating response to ICI in mRCC patients. Citation Format: Jin-Sung Chung, Vijay Ramani, Ponciano D. Cruz, Hans J. Hammers, Kiyoshi Ariizumi. Elevated serum DC-HIL is associated with poor response to immune checkpoint inhibitors (ICI) in metastatic renal cell carcinoma (mRCC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1258.

Abstract 2862: Novel immune checkpoint protein CNTN4 and the preclinical efficacy of affinity matured anti-CNTN4 antibody GENA-104A16

Abstract The immunotherapeutic treatment has profoundly improved the clinical outcomes in patients with advanced cancers. However, most patients still have not responded to immune checkpoint inhibitor (ICI) treatment. Thus, it is still urgent to find novel treatments for patients who have no response to ICI and acquire ICI resistance. We previously suggested that contactin 4 (CNTN4), known initially to act as an axon guidance molecule during neural development, is a novel inhibitory immune checkpoint protein. In addition, we confirmed that CNTN4 is highly expressed on the various types of human tumor tissue, and anti-CNTN4 antibodies, GENA-104A07 and GENA-104A11, show the anti-tumor efficacy by enhancing T cell activity. In the present study, we describe the role of amyloid precursor protein (APP) expressed on T cells as a binding partner of CNTN4 and the preclinical characterization of GENA-104A16 as an immune-oncology drug candidate targeting CNTN4. Firstly, we investigated the APP expression on T cells and found that APP was detected in T cells' membrane and cytosolic fraction. Its expression level was higher on activated T cells. In addition, we observed that the immune-suppressive activity of CNTN4 on APP KO T cells was significantly decreased compared with APP WT T cells, which means APP as a binding partner of CNTN4 is a core molecule for transmitting immunosuppressive signal of CNTN4 to T cells. GENA-104A16 is a humanized antibody and binds to human and mouse CNTN4 with high binding affinity, which is matured from GENA-104A07 and GENA-104A11. In the in vitro functional assays, GENA-104A16 showed the improved effects on the restoration of T cell proliferation and activation (i.e., inflammatory cytokine releases from T cells and T cell activity-related signaling cascade) suppressed by CNTN4 and on CTL (cytotoxic T lymphocytes)-mediated killing for human cancer cell lines expressing CNTN4. In line with these effects, GENA-104A16 produced higher anti-tumor effects than GENA-104A11 in the CT26 syngeneic mouse colon cancer model. To identify the in vivo immune modulatory function of GENA-104A16, we analyzed the proportion of tumor-infiltrated T cells, Treg cells, and T cell subsets expressing perforin and granzyme B in CT26 tumor tissues. As a result, the population of CD4+ T cells, CD8+ T cells, and cytotoxic CD8+ T cells expressing perforin or granzyme B tended to increase in the tumors of GENA-104A16 treated mice while decreasing the FoxP3+CD25+ Treg population. Interestingly, GENA-104A16 treatment showed better anti-tumor effects together with the elevated level of CD8+ T cells expressing perforin and granzyme B than atezolizumab treatment. Overall, these preclinical studies demonstrate that GENA-104A16 is a promising blocking antibody for CNTN4-mediated immune suppression and can serve as an effective immune-oncology drug for patients with cancer that highly express CNTN4. Citation Format: Mi Young Cha, Hnkyung yu, Bu-Nam Jeon, Hyunuk Kim, Youngeun Ha, Yunyeon Kim, Joo-Yeon Chung, Soojung Moon, Hyunseong Youn, Han-sol Kim, Kyung Mi Park, Hansoo Park. Novel immune checkpoint protein CNTN4 and the preclinical efficacy of affinity matured anti-CNTN4 antibody GENA-104A16 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2862.

Abstract 5641: Tumor cell intrinsic factors in colorectal cancer immune evasion

Abstract The poor response of most colorectal cancer (CRC) patients to immunotherapy is a major unmet clinical need. Although early detection through screening has reduced CRC incidence, the prognosis for metastatic CRC is poor. In the past decade, immune checkpoint inhibitors (ICIs) have been a major clinical breakthrough with promising clinical benefits in many cancer types, but its efficacy is limited in most (~85%) CRC patients. ICIs preferentially have robust responses from tumors with pre-existing T cell infiltration. However, most CRC lacks robust T-cell infiltration due to immune evasion mechanisms. Therefore, it is crucial to characterize factors shaping immune evasion to improve the response to ICIs. We hypothesize that targeting tumor-cell intrinsic factors can overcome T cell exclusion and will sensitize the tumor to ICIs. To elucidate the factors underlying ICI resistance, it is critical that preclinical models faithfully recapitulate the tumor physiology and genetics of the human disease. Therefore, we developed a tumor organoid (tumoroids) model system adapted from Jacks lab that harbors shApc, KrasG12D, p53-/- and Smad4-/- (shAKPS) mutations, which are co-mutated with high frequency and associated with poor prognosis. We demonstrated that tumoroids with only shApc and KrasG12D mutations can form a solid tumor in two weeks. Addition of p53-/- and Smad4-/- mutations drives invasiveness and metastasis. The shAKPS tumoroids present key features of advanced CRC that are unresponsive to ICIs including invasive tumor, metastasis, and T cell exclusion. Using CRISPR/Cas9 screening and integrative immune score analysis, we identified potential immune evasive genes. To define their expression profile in the tumor, we performed TCGA data analysis in fourteen different cancer types. Furthermore, we performed correlation tests to determine their role in immune cell infiltration and T cell dysfunction. Our results show that these immune suppressive genes are overexpressed in tumor tissues, and negatively correlate with CD8+ T cell infiltration. Our findings suggest that overexpression of immune suppressive genes in cancer cells may cause T cell dysfunction and exclusion in tumors. Furthermore, the functional role of these immune suppressive genes will be characterized using shAKPS mutant organoids and in vivo orthotopic CRC tumor models. Citation Format: Dechen Wangmo, Xianda Zhao, Angelo Yuan, Travis Gates, Subree Subramanian. Tumor cell intrinsic factors in colorectal cancer immune evasion [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5641.

Roles of Cadherin2 in Thyroid Cancer.

BackgroundThe majority of drug-resistant cells in Thyroid cancer (THCA) tend to exhibit an Epithelial mesenchymal transition (EMT) phenotype, and abnormal expression of the cell adhesion molecule Cadherin2 (CDH2) is a hallmark of EMT. However, the roles of CDH2 in THCA and its underlying mechanisms are unknown.MethodsWe analyzed the CDH2 expression in The Cancer Genome Atlas (TCGA) database and screened for genes positively associated with CDH2. Small interfering RNA and cell transfection were used for knocking down CDH2 in THCA cells, cell counting kit-8 (CCK-8) assay and immunofluorescence to detect cell proliferation. Binding miRNAs of CDH2 and CDH2-associated genes were predicted using the Encyclopedia of RNA Interactomes (ENCORI) database. The expression of genes in clinical THCA tissues was investigated from the Human Protein Atlas (HPA) database and validated by qRT-PCR. We conducted the cell functions pathways of CDH2 and CDH2-associated gene FRMD3 by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. We also showed the correlation between CDH2 and FRMD3 expression and tumor immune infiltration.ResultsThe expression of CDH2 was significantly higher in THCA tumor tissues compared to normal tissues. Moreover, there were strongly associations of CDH2 expression with the stages T and N. Cellular function assays showed that CDH2 exerted its growth-promoting activity of THCA. To better understand how CDH2 was regulated in THCA, we sought genes associated with CDH2. Correlation analysis revealed that there were negative correlations between genes (CDH2, FRMD3) and miRNAs (hsa-miR-410-3p, hsa-miR-411-5p, hsa-miR-299-5p). Moreover, CDH2 and FRMD3 expression were significantly higher in tumor tissues than in normal tissues, while hsa-miR-410-3p, hsa-miR-411-5p and hsa-miR-299-5p were significantly decreased in tumor tissues compared with normal tissues in THCA. GO and KEEG results showed that CDH2 and FRMD3 were strongly associated with immune-related functions. High expression of CDH2 and FRMD3 was linked to the suppression of immune cells. There were strong negativity correlations between CDH2, FRMD3 and T-cell exhaustion factors.ConclusionOur data indicated that CDH2 and CDH2-related gene FRMD3 might have the critical effects on altering tumors becoming ‘cold tumors’ eventually leading to immune checkpoint inhibitor resistance.

Cell-free DNA analysis as a molecular tool to monitor response to immune checkpoint inhibition in endometrial cancer.

5592 Background: Immune checkpoint inhibitors (ICI) targeting PD-1 have meaningful activity in microsatellite instability high (MSI-H), hypermutated or mismatch repair deficient (dMMR) advanced endometrial cancer (EC). We investigated if high-depth circulating cell free (cf)DNA sequencing can be used to assess MSI status and monitor ICI response in EC patients enrolled in a phase II trial (NCT03241745). Methods: Patients with recurrent/persistent MSI-H/dMMR/hypermutated EC with measurable disease and ≥1 prior lines of cytotoxic therapy were treated from 06/2018-01/2022 with nivolumab until progression of disease (PD) or unacceptable toxicity. Radiologic tumor response was assessed every 12 wks by RECIST 1.1 criteria.Pre-treatment ECs and matched normal blood-derived DNA were subjected to whole-exome sequencing (WES); cfDNA from plasma at baseline, 2 wks and every 6 wks thereafter was subjected to high-depth MSK-ACCESS sequencing (129 genes). MSI in WES and cfDNA was calculated by MSIsensor and ADMIE, respectively. Results: Ten patients with ≥10 ng cfDNA at baseline and 2 weeks after nivolumab initiation were included. Most (80%) had grade 3 endometrioid EC; 70% had MLH1 hypermethylated EC. Two patients had partial response (PR), 3 had stable disease (SD) and 5 had PD on nivolumab. A high-depth sequencing assay captured somatic mutations in cfDNA at baseline in all patients (median, 29.5; range, 2-75). Median circulating tumor (ct)DNA fraction in cfDNA was 13.1% at baseline (range, 0.0-86.0%). In 8 cases, ctDNA fraction was sufficient to perform MSI assessment. Liquid biopsy MSI status matched tumor MSI status assessed by WES: in 7 patients with MSI-H disease by tumor WES, cfDNA MSI status was also MSI-H ( > 0; range, 0.21-5.46); in 1 patient with MSI-low but hypermutated tumor, cfDNA MSI was 0.0. In all cases, changes in ctDNA fractions reflected ICI response. Median ctDNA fraction percent change from week 0 to week 8 was -51.6% (IQR, -6.2, -85.1) in patients with PR and SD vs +17.7% (IQR, -6.6, +356.6) in patients with PD (p = 0.08). In patients with PR, ctDNA fraction decreased at week 2 and stayed low at week 8 and weeks 32-55 of nivolumab in concordance with ongoing response. In 3 patients with SD, ctDNA fractions decreased by week 2. In 1 patient with SD at week 8 and PD at week 22, ctDNA fraction increased from week 8 to week 20. In 5 patients with PD, 4 had increased ctDNA fraction by week 8. The last patient had a stable ctDNA fraction but increasing allele frequency of 2 truncating B2M alterations, possibly associated with ICI resistance. Conclusions: In patients with advanced hypermutated ECs, cfDNA sequencing can be used to accurately detect MSI status. Early changes in ctDNA fraction may be associated with durable response to ICI or may anticipate radiological progression. Future studies may use ctDNA to assess mechanisms of ICI resistance and offer opportunities for adaptive therapy intervention. Clinical trial information: NCT03241745.

Genomic characterization of immune checkpoint inhibitor resistance genes and hyperprogression genes in advanced solid tumors.

e14582 Background: Immune checkpoint inhibitors have been widely used in the systematic treatment of various advanced solid tumors, but they show poor efficacy or lead to hyperprogression in some patients. Some studies reported that EGFR mutations, ALK fusion, interferon pathway or Wnt signal pathway gene mutations might reduce the efficacy of immunotherapy and lead to tumor hyperprogression. The aim of this study was to determine the frequency of gene variations associated with immunotherapy resistance or hyperprogression in advanced solid tumors. Methods: The tumor tissues or blood samples of 111 patients with advanced solid tumors were collected. The tumor tissues were sequenced by targeted next-generation sequencing (55 genes, Illumina novaseq 6000), MSI (PCR) and PD-L1 detection (IHC). Blood cfdna was extracted and sequenced by targeted next-generation sequencing (55 genes, Illumina novaseq 6000). Results: A total of 111 patients with advanced solid tumors were included in the study, including 34 patients with colorectal cancer, 27 patients with hepatobiliary tumors, 18 patients with gastric cancer, 15 patients with urothelial carcinoma, and 17 patients with other solid tumors. Among the 82 samples tested for MSI, there were 77 cases of MSS (93.9%), 1 case of MSI-L (1.2%), and 4 cases of MSI-H (4.9%). 44 samples were tested for PD-L1 expression. 33 (75%) had PD-L1 expression < 1%, and 11 (25%) had PD-L1 expression greater than 1% but less than 49%. Among the genes related to immunotherapy, the mutations of genes related to cell growth or cell cycle regulation (EGFR, ALK, CDKN2A and CCND1) accounted for 3 (2.7%), 5 (4.5%), 12 (10.8%) and 5 (4.5%), respectively. The mutation of antigen presentation related gene (B2M) accounted for 3 (2.7%). The mutations of interferon signaling pathway related genes (JAK1, JAK2, JAK3 and IFNGR1) accounted for 2 (1.8%), 5 (4.5%), 1 (0.9%) and 1 (0.9%), respectively. The mutations in Wnt signaling pathway related genes (APC, AXIN1, CTNNB1) accounted for 41 (36.9%), 5 (4.5%) and 7 (6.3%). The mutations of tumor suppressor genes (PTEN, STK11 and PTPN2) accounted for 9 (8.1%), 1 (0.9%) and 3 (2.7%). Mutations in other genes (APLNR, DNMT3a, MDM2) accounted for 1 (0.9%), 6 (5.4%) and 7 (6.3%). Conclusions: Our study shows that in patients with advanced solid tumors, there are multiple gene variants related to drug resistance or hyperprogression of tumor immune checkpoint inhibitor treatment, suggesting that it may be the reason for the difference in the efficacy of immunotherapy. It is necessary to further study the efficacy of immunotherapy in patients with different gene mutations and the combination of immune checkpoint inhibitors for patients with different pathway mutations.

Genomic characterization of immune checkpoint inhibitor resistance genes and hyperprogression related genes in advanced lung cancer.

e21042 Background: Immune checkpoint inhibitors have been widely used in the treatment of advanced lung cancer, but immunotherapy still shows poor efficacy or leads to hyperprogression in some patients. Some studies demonstrated that EGFR mutations, ALK fusion, interferon pathway gene mutation, and Wnt signal pathway mutation might reduce the efficacy of immunotherapy and lead to tumor hyperprogression. The aim of this study was to determine the frequency of gene variations associated with immunotherapy resistance or hyperprogression in patients with advanced lung cancer. Methods: The tumor tissues or blood samples of 129 patients with advanced lung cancer were collected. The tumor tissues were sequenced by targated next-generation sequencing (55 genes, Illumina novaseq 6000), MSI (PCR), and PD-L1 detection (IHC). Blood cfdna was extracted and sequenced by targeted next-generation sequencing (55 genes, Illumina novaseq 6000). Results: A total of 129 patients with advanced lung cancer were included in the study, including 126 patients with non-small cell lung cancer and 3 patients with small cell lung cancer. Tissue was available for testing in 113 patients, blood samples were collected from 106 patients, and cerebrospinal fluid samples were collected from 1 patient. Among 85 samples tested for MSI, there were 81 cases of MSS (95.3%), 3 cases of MSI-L(3.5%), and 1 case of MSI-H (1.2%). PD-L1 expression was detected in 60 samples. 23 samples (38.3%) had PD-L1 expression < 1%, 31 samples (51.7%) had PD-L1 expression greater than 1% but less than 49%, and 6 samples (10%) had PD-L1 expression > 50%. Among the genes related to immunotherapy, the mutations of genes related to cell growth or cell cycle regulation (EGFR, ALK, CDKN2A, CCND1) accounted for 86 (66.7%), 12 (9.3%), 15 (11.6%), 8 (6.2%), respectively. The mutation of antigen presentation related gene (B2M) accounted for 2 (1.6%). The mutations of interferon signaling pathway related genes (JAK1, JAK2, JAK3, IFNGR1, PIAS4 and SOCS1) accounted for 6 (4.7%), 7 (5.4%), 3 (2.3%), 3 (2.3%), 1 (0.8%) and 1 (0.8%), respectively. Wnt signaling pathway related genes (APC, AXIN1, CTNNB1) accounted for 8 (6.2%), 2 (1.6%) and 4 (3.1%). Mutations in tumor suppressor genes (PTEN, STK11, KEAP1, PTPN2) accounted for 4 (3.1%), 8 (6.2%), 6 (4.7%) and 3 (2.3%). Mutations in other genes (APLNR, DNMT3A, MDM2, MDM4) accounted for 3 (2.3%), 1 (0.8%), 7 (5.4%) and 1 (0.8%). Conclusions: Our study shows that in patients with advanced lung cancer, there are multiple gene variants related to drug resistance or hyperprogression of immune checkpoint inhibitors, suggesting that this may be the reason for the difference in immunotherapy efficacy in patients. It is necessary to further study the efficacy of immunotherapy in patients with different gene mutations and the combination of immune checkpoint inhibitors for patients with different pathway mutations.

A deep learning approach utilizing clinical and molecular data for identifying prognostic biomarkers in patients treated with immune checkpoint inhibitors: An ORIEN pan-cancer study.

2619 Background: Immune checkpoint inhibitors (ICIs) have made significant improvements in the treatment of cancer patients (pts), but many continue to experience primary or secondary resistance. Here, we leveraged clinical and genomic data to identify prognostic biomarkers in pts treated with ICIs utilizing a pan-cancer approach. Methods: Pts were enrolled to the Total Cancer Care protocol across 18 cancer centers within the Oncology Research Information Exchange Network (ORIEN). RNA-seq was performed on tumors following the RSEM pipeline and gene expressions were quantified as Transcript Per Million (TPM) and were logarithmically normalized. An Auto-Encoder Survival Deep Network (AE-SDN) architecture was developed that combined the reconstruction loss of AE with Cox regression for modeling time to event. For comparison, immunoscore for each pt was calculated based on the estimated densities of tumor CD3+ and CD8+ T cells (Galon, 2020) utilizing CIBERSORTx. The quality of overall survival (OS) predictions was assessed using Harrell’s concordance index (C-index). Log-rank test was used to assess stratified group differences (by ICI or cancer histology) along with Kaplan-Meier (KM) survival analysis of AE-SDN and immunoscore. Results: Pts (n=522) with 4 cancer types including melanoma (n=125), renal cell carcinoma (n=149), non-small cell lung cancer (n=128) and head and neck cancer (n=120) treated with 6 ICI regimens were included in this analysis. ICI regimens were nivolumab (n=219), pembrolizumab (n=202), ipilimumab+nivolumab (n=69), ipilimumab (n=30), avelumab (n=1) and cemiplimab (n=1). The Table summarizes the overall C-index and associated 95% CIs and log-rank P values for the entire cohort (regardless of histology) resulting from our proposed AE-SDN model and the separate estimated immunoscore categorization. AE-SDN top selected genes were mostly related to immunity, carcinogenesis and tumor suppression. The corresponding KM plots showed significantly wider separations of the survival curves in favor of our proposed AE-SDN model relative to the immunoscore with more than 20% improvement in prediction power. Conclusions: Deep network machine learning analysis is a promising approach to identifying relevant prognostic biomarkers in cancer pts treated with ICI. This may lead to novel therapeutic predictive signatures and identification of mechanisms of ICI resistance. Our AE-SDN gene expression signature was significantly prognostic and outperformed the estimated CD3+, CD8+ T Cell immunoscore. Further refinements to our prediction power are ongoing along with more advanced neural network architectures to elucidate related functional pathways. [Table: see text]

Landscape of fibroblast growth factor receptor (FGFR) genomic alterations (GA) in urothelial bladder cancer (UBC).

4568 Background: Urothelial bladder carcinomas (UBC) with genomic alterations (GA) in the Fibroblast Growth Factor Receptor ( FGFR) genes have been postulated to be less responsive to immune checkpoint inhibitors (ICI). Immune microenvironment of these tumors could be altered due to suppression of interferon signaling pathways. Here, we present comprehensive genomic profiling (CGP) of FGFR altered UBC to study the underlying immunogenomic mechanisms of response and resistance. Methods: 4,035 UBC underwent hybrid capture based CGP. Tumor mutational burden (TMB) was determined on up to 1.1 Mbp of sequenced DNA and microsatellite instability (MSI) was determined using 114 loci. Programmed death ligand (PD-L1) expression in tumor cells was assessed by IHC (Dako 22C3). Results: 894 (22%) of UBC featured FGFR GA ( FGFR1 3.7%; FGFR2 1.1%; FGFR3 17.4%). Gender and age distribution was similar in all groups. FGFR3 cases had lower GA/tumor and 14.7% GA were fusions. ERBB2 amplification was significantly higher in FGFR1/2 altered UBC compared with FGFR3 altered UBC. MTOR pathway GA were highest in FGFR3 altered UBC. FGFR3 altered UBC featured significantly higher frequencies of biomarkers predicting resistance to ICI including lower TMB, lower PD-L1 expression and higher frequencies of GA in MDM2. FGFR3 driven UBC also features significantly higher frequencies of CDKN2A/B loss and MTAP loss which have also recently been linked to IO drug resistance. Conclusions: UBC harboring FGFR GA have increased frequency of alterations that have been linked to ICI resistance. Further evaluation of FGFR-based biomarkers in UBC clinical trials focused on the assessment of the patient response to ICI appears warranted. [Table: see text]

Multi-omic and spatial dissection of immunotherapy response groups in non–small cell lung cancer (NSCLC).

8544 Background: Immune checkpoint inhibitors (ICI) have shown durable benefit in a subset of non-small cell lung cancer (NSCLC) patients. The composition of the tumour microenvironment (TME) is becomingly increasingly recognised as an important factor to predict response to therapy. Methods: Here, we applied digital spatial profiling of the tumour and stromal compartments from a 2nd line NSCLC ICI-treated cohort (n = 41 patient) and standard of care (SOC), platinum treated NSCLC cohort (n = 47), to identify tissue-based signatures of response to therapy. Results: We demonstrate by mIHC that the interaction of CD68+ macrophages with PD1+, FoxP3+ cells is significantly enriched in ICI refractory tumours (p = 0.012). Patients sensitive to ICI therapy expressed higher levels of IL2 receptor alpha (CD25, p = 0.028) within the tumour compartments, which corresponded with the increased expression of IL2 mRNA (p = 0.001) within their stroma. Immuno-inhibitory markers CTLA-4 (p = 0.021) and IDO-1 (p = 0.023) were supressed in ICI-responsive patients. Tumour CD44 (p = 0.02) was depleted in the response group and corresponded inversely with significantly higher stromal expression of one of its ligands, SPP1 (osteopontin, p = 0.008). Analysis of dysregulated transcripts indicated the potential inhibition of stromal interferon-gamma (IFNγ) activity, estrogen-receptor and Wnt-1 signalling activity within the tumour cells of ICI responsive patients. Cox survival analysis indicated tumour CD44 expression was associated with poorer prognosis (HR = 1.61, p = 0.01), consistent with its depletion in ICI sensitive patients. Similarly, stromal CTLA-4 (HR = 1.78, p = 0.003) and MDSC/M2 macrophage marker ARG1 (HR = 2.37, p = 0.01) were associated with poorer outcome while BAD (HR = 0.5, p = 0.01) appeared protective. The SOC cohort paralleled similar roles for immune checkpoints and pro-apoptotic markers, with LAG3 (HR = 3.81, p = 0.04) indicating poorer outcome, and BIM (HR = 0.16, p = 0.014) with improved outcome. Interestingly, stromal mRNA for E-selectin (HR = 652, p = 0.001), CCL17 (HR = 70, p = 0.006) and MTOR (HR = 1065, p = 0.008) were highly associated with poorer outcome in ICI treated patients, indicating pro-tumourigenic features in the tumour microenvironment that may facilitate ICI resistance. Conclusions: Through multi-modal approaches, we have dissected the characteristics of NSCLC treatment groups and provide evidence for the role of several markers including IL2, CD25, CD44 and SPP1 in the efficacy of current generations of ICI therapy.

Overcoming Resistance to Checkpoint Inhibitors: Natural Killer Cells in Non-Small Cell Lung Cancer.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatments over the last 10 years, with even increasing indications in many neoplasms. Non-small cell lung cancer (NSCLC) is considered highly immunogenic, and ICIs have found a wide set of applications in this area, in both early and advanced lines of treatment, significantly changing the prognosis of these patients. Unfortunately, not all patients can benefit from the treatment, and resistance to ICIs can develop at any time. In addition to T lymphocytes, which are the major target, a variety of other cells present in the tumor microenvironment (TME) act in a complex cross-talk between tumor, stromal, and immune cells. An imbalance between activating and inhibitory signals can shift TME from an “anti-” to a “pro-tumorigenic” phenotype and vice versa. Natural killer cells (NKs) are able to recognize cancer cells, based on MHC I (self and non-self) and independently from antigen presentation. They represent an important link between innate and adaptive immune responses. Little data are available about the role of pro-inflammatory NKs in NSCLC and how they can influence the response to ICIs. NKs express several ligands of the checkpoint family, such as PD-1, TIGIT, TIM-3, LAG3, CD96, IL1R8, and NKG2A. We and others have shown that TME can also shape NKs, converting them into a pro-tumoral, pro-angiogenic “nurturing” phenotype through “decidualization.” The features of these NKs include expression of CD56, CD9, CD49a, and CXCR3; low CD16; and poor cytotoxicity. During ICI therapy, tumor-infiltrating or associated NKs can respond to the inhibitors or counteract the effect by acting as pro-inflammatory. There is a growing interest in NKs as a promising therapeutic target, as a basis for adoptive therapy and chimeric antigen receptor (CAR)-NK technology. In this review, we analyzed current evidence on NK function in NSCLC, focusing on their possible influence in response to ICI treatment and resistance development, addressing their prognostic and predictive roles and the rationale for exploiting NKs as a tool to overcome resistance in NSCLC, and envisaging a way to repolarize decidual NK (dNK)-like cells in lung cancer.

LKB1: Can We Target an Hidden Target? Focus on NSCLC.

LKB1 (liver kinase B1) is a master regulator of several processes such as metabolism, proliferation, cell polarity and immunity. About one third of non-small cell lung cancers (NSCLCs) present LKB1 alterations, which almost invariably lead to protein loss, resulting in the absence of a potential druggable target. In addition, LKB1-null tumors are very aggressive and resistant to chemotherapy, targeted therapies and immune checkpoint inhibitors (ICIs). In this review, we report and comment strategies that exploit peculiar co-vulnerabilities to effectively treat this subgroup of NSCLCs. LKB1 loss leads to an enhanced metabolic avidity, and treatments inducing metabolic stress were successful in inhibiting tumor growth in several preclinical models. Biguanides, by compromising mitochondria and reducing systemic glucose availability, and the glutaminase inhibitor telaglenastat (CB-839), inhibiting glutamate production and reducing carbon intermediates essential for TCA cycle progression, have provided the most interesting results and entered different clinical trials enrolling also LKB1-null NSCLC patients. Nutrient deprivation has been investigated as an alternative therapeutic intervention, giving rise to interesting results exploitable to design specific dietetic regimens able to counteract cancer progression. Other strategies aimed at targeting LKB1-null NSCLCs exploit its pivotal role in modulating cell proliferation and cell invasion. Several inhibitors of LKB1 downstream proteins, such as mTOR, MEK, ERK and SRK/FAK, resulted specifically active on LKB1-mutated preclinical models and, being molecules already in clinical experimentation, could be soon proposed as a specific therapy for these patients. In particular, the rational use in combination of these inhibitors represents a very promising strategy to prevent the activation of collateral pathways and possibly avoid the potential emergence of resistance to these drugs. LKB1-null phenotype has been correlated to ICIs resistance but several studies have already proposed the mechanisms involved and potential interventions. Interestingly, emerging data highlighted that LKB1 alterations represent positive determinants to the new KRAS specific inhibitors response in KRAS co-mutated NSCLCs. In conclusion, the absence of the target did not block the development of treatments able to hit LKB1-mutated NSCLCs acting on several fronts. This will give patients a concrete chance to finally benefit from an effective therapy.

Analysis of biomarkers in melanoma patients receiving ICI treatments: pre- vs post in responders and progressors

Abstract Markers of immune related adverse events and response in patients treated with immune checkpoint inhibitors (ICI) may shed light into ICI resistance, T cell exhaustion and other combinatorial therapies. The elevated levels of these biomarkers have potential to predict if PD-1 or PD-1/CTLA-4 antagonist combination will be effective in a certain Melanoma patient. Therefore, it may potentially guide healthcare providers to change treatment plans. In this study, the ICI treatments we focused on were PD-1 or combination of PD-1/CTLA-4 blockades. The measurement of the biomarkers was conducted at Mayo Clinic, from serum samples obtained in 2 time points, pre-treatments and 2–3 months after the first ICI treatments. Validated IVD kits were used per manufacture’s instruction. Biomarkers could be measured using stored frozen serum samples according to the instructions on how the biomarkers will be measured. We investigated 13 biomarkers in the sera of 76 melanoma patients who received immune checkpoint therapies. The biomarkers tested were, Human ELAFIN ELISA, Human IL-18 ELISA, Reg3α + Universal kit, Anti-Nuclear Antibody Test System, FLUORO AID-1 Test for anti-mitochondrial antibodies, anti-smooth muscle antibodies and anti-parietal cell antibodies, Anti-MDA5 ELISA Kit, Anti-synthetase ELISA Skin, Antineutrophil cytoplasmic antibodies MPO-ANCA ELISA, Antineutrophil cytoplasmic antibodies PR3-ANCA ELISA, Dsg1, Dsg3 ELISA, BP180, BP230, type-VII collagen. When compared with the samples obtained before treatments, IL-18 levels significantly elevated (p value < 0.0001) in post treatment samples of non-responders. Further studies are needed to confirm if elevated IL-18 contribute to the biology of resistance to ICI therapies. Supported by MBLI

Liquid Biopsy Assessment of Circulating Tumor Cell PD-L1 and IRF-1 Expression in Patients with Advanced Solid Tumors Receiving Immune Checkpoint Inhibitor.

Reliable biomarkers that can be serially monitored to predict treatment response to immune checkpoint inhibitors (ICIs) are still an unmet need. Here, we present a multiplex immunofluorescence (IF) assay that simultaneously detects circulating tumor cells (CTCs) and assesses CTC expression of programmed death ligand-1 (PD-L1) and interferon regulatory factor 1 (IRF-1) as a candidate biomarker related to ICI use. To assess the potential of CTC PD-L1 and IRF-1 expression as candidate biomarkers for patients with advanced epithelial solid tumors receiving ICIs. We tested the IF CTC assay in a pilot study of 28 patients with advanced solid tumors who were starting ICI. Blood for CTC evaluation was obtained prior to starting ICI, after a single cycle of therapy, and at the time of radiographic assessment or treatment discontinuation. At baseline, patients with 0-1 CTCs had longer progression-free survival (PFS) compared to patients with ≥ 2 CTCs (4.3 vs 1.3 months, p = 0.01). The presence of any PD-L1+ CTCs after a single dose of ICI portended shorter PFS compared to patients with no CTCs or PD-L1- CTCs (1.2 vs 4.2 months, p = 0.02); the presence of any PD-L1+ or IRF-1+ CTCs at time of imaging assessment or treatment discontinuation also was associated with shorter PFS (1.9 vs 5.5 months, p < 0.01; 1.6 vs 4.7 months, p = 0.05). CTC PD-L1 and IRF-1 expression did not correlate with tumor tissue PD-L1 or IRF-1 expression. Strong IRF-1 expression in tumor tissue was associated with durable (≥1 year) radiographic response (p = 0.02). Based on these results, CTC PD-L1 and IRF-1 expression is of interest in identifying ICI resistance and warrants further study.

Tumors bearing defective transcription elongation are immune hot but resistant to immune checkpoint inhibitors

Abstract Tumors infiltrated with abundant T lymphocytes are generally thought to respond to immune checkpoint inhibitors (ICI). However, a significant proportion of immune hot tumors are resistant to ICI. The immune nature of such tumors is poorly understood. We recently reported a tumor type that is defective in transcription elongation (TEdef) and irresponsive to ICI in several clinical cohorts. Here, we show that TEdef tumors are unexpectedly infiltrated with cytotoxic T cells (CTLs) in patients and in animal models. Mechanistically, T cell infiltration is facilitated by cytoplasmic DNA/double strand RNA-nucleic acid sensing-TBK1-ccl5/cxcl/9/10 signaling cascade. However, single-cell RNA sequencing combined with flow cytometry reveals that CTLs in TEdef tumors are exhausted. Furthermore, immune suppressive regulatory T cells are enriched in TEdef tumors. ICI treatment of TEdef tumors in mice and human patients fails to further induce T cell infiltration. This study reveals a mechanism underlying inert inflammation and ICI resistance of TEdef tumors. We suggest that TEdef, alongside the surrogate markers of tumor mutational burden and CTLs, should be assessed in immunotherapy-candidate patients. Supported by 5R01CA234038-03

Integrated analysis of single-cell and bulk RNA sequencing data reveals a pan-cancer stemness signature predicting immunotherapy response

BackgroundAlthough immune checkpoint inhibitor (ICI) is regarded as a breakthrough in cancer therapy, only a limited fraction of patients benefit from it. Cancer stemness can be the potential culprit in ICI resistance, but direct clinical evidence is lacking.MethodsPublicly available scRNA-Seq datasets derived from ICI-treated patients were collected and analyzed to elucidate the association between cancer stemness and ICI response. A novel stemness signature (Stem.Sig) was developed and validated using large-scale pan-cancer data, including 34 scRNA-Seq datasets, The Cancer Genome Atlas (TCGA) pan-cancer cohort, and 10 ICI transcriptomic cohorts. The therapeutic value of Stem.Sig genes was further explored using 17 CRISPR datasets that screened potential immunotherapy targets.ResultsCancer stemness, as evaluated by CytoTRACE, was found to be significantly associated with ICI resistance in melanoma and basal cell carcinoma (both P < 0.001). Significantly negative association was found between Stem.Sig and anti-tumor immunity, while positive correlations were detected between Stem.Sig and intra-tumoral heterogenicity (ITH) / total mutational burden (TMB). Based on this signature, machine learning model predicted ICI response with an AUC of 0.71 in both validation and testing set. Remarkably, compared with previous well-established signatures, Stem.Sig achieved better predictive performance across multiple cancers. Moreover, we generated a gene list ranked by the average effect of each gene to enhance tumor immune response after genetic knockout across different CRISPR datasets. Then we matched Stem.Sig to this gene list and found Stem.Sig significantly enriched 3% top-ranked genes from the list (P = 0.03), including EMC3, BECN1, VPS35, PCBP2, VPS29, PSMF1, GCLC, KXD1, SPRR1B, PTMA, YBX1, CYP27B1, NACA, PPP1CA, TCEB2, PIGC, NR0B2, PEX13, SERF2, and ZBTB43, which were potential therapeutic targets.ConclusionsWe revealed a robust link between cancer stemness and immunotherapy resistance and developed a promising signature, Stem.Sig, which showed increased performance in comparison to other signatures regarding ICI response prediction. This signature could serve as a competitive tool for patient selection of immunotherapy. Meanwhile, our study potentially paves the way for overcoming immune resistance by targeting stemness-associated genes.

Discovery of Biomarkers of Resistance to Immune Checkpoint Blockade in NSCLC Using High-Plex Digital Spatial Profiling

IntroductionDespite the clinical efficacy of immune checkpoint inhibitors (ICIs) in NSCLC, only approximately 20% of patients remain disease-free at 5 years. Here, we use digital spatial profiling to find candidate biomarker proteins associated with ICI resistance. MethodsPretreatment samples from 56 patients with NSCLC treated with ICI were analyzed using the NanoString GeoMx digital spatial profiling method. A panel of 71 photocleavable oligonucleotide-labeled primary antibodies was used for protein detection in four molecular compartments (tumor, leukocytes, macrophages, and immune stroma). Promising candidates were orthogonally validated with quantitative immunofluorescence. Available pretreatment samples from 39 additional patients with NSCLC who received ICI and 236 non–ICI-treated patients with operable NSCLC were analyzed to provide independent cohort validation. ResultsBiomarker discovery using the protein-based molecular compartmentalization strategy allows 284 protein variables to be assessed for association with ICI resistance by univariate analysis using continuous log-scaled data. Of the 71 candidate protein biomarkers, CD66b in the CD45+CD68 molecular compartment (immune stroma) predicted significantly shorter overall survival (OS) (hazard ratio [HR] 1.31, p = 0.016) and was chosen for validation. Orthogonal validation by quantitative immunofluorescence illustrated that CD66b was associated with resistance to ICI therapy but not prognostic for poor outcomes in untreated NSCLC (discovery cohort [OS HR 2.49, p = 0.026], validation cohort [OS HR 2.05, p = 0.046], non–ICI-treated cohort [OS HR 1.67, p = 0.06]). ConclusionsUsing the technique, we have discovered that CD66b expression is indicative of resistance to ICI therapy in NSCLC. Given that CD66b identifies neutrophils, further studies are warranted to characterize the role of neutrophils in ICI resistance.