Gnjatic, Sacha

Abstract To investigate the cellular and molecular mechanisms associated with targeting CD30-expressing Hodgkin lymphoma (HL) and immune checkpoint modulation induced by combination therapies of CTLA4 and PD1, we leveraged Phase 1/2 multicenter open-label trial NCT01896999 that enrolled patients with refractory or relapsed HL (R/R HL). Using peripheral blood, we assessed soluble proteins, cell composition, T-cell clonality, and tumor antigen-specific antibodies in 54 patients enrolled in the phase 1 component of the trial. NCT01896999 reported high (>75%) overall objective response rates with brentuximab vedotin (BV) in combination with ipilimumab (I) and/or nivolumab (N) in patients with R/R HL. We observed a durable increase in soluble PD1 and plasmacytoid dendritic cells as well as decreases in plasma CCL17, ANGPT2, MMP12, IL13, and CXCL13 in N-containing regimens (BV + N and BV + I + N) compared with BV + I (P < 0.05). Nonresponders and patients with short progression-free survival showed elevated CXCL9, CXCL13, CD5, CCL17, adenosine–deaminase, and MUC16 at baseline or after one treatment cycle and a higher prevalence of NY-ESO-1-specific autoantibodies (P < 0.05). The results suggest a circulating tumor-immune-derived signature of BV ± I ± N treatment resistance that may be useful for patient stratification in combination checkpoint therapy. Significance: Identification of multi-omic immune markers from peripheral blood may help elucidate resistance mechanisms to checkpoint inhibitor and antibody–drug conjugate combinations with potential implications for treatment decisions in relapsed HL.

8634 Background: Patients with unresectable non-small cell lung cancer (NSCLC) with an inadequate response to immune checkpoint inhibitors (ICI) have limited therapeutic options and expected median overall survival (mOS) of 11.6 to 14.5m (PMID: 35658002 ). The immunosuppressive tumor microenvironment and the lack of a specific T cell response underpin inadequate clinical response. CAN-2409 is a replication-defective adenovirus encoding the HSV-tk gene. Transduced cells activate orally delivered valacyclovir, resulting in immunogenic cell death, and in situ immunization against the patient’s tumor antigens, eliciting a specific immune response against the injected tumor and uninjected metastases. Methods: NCT04495153 is an open-label, phase 2 clinical trial of CAN-2409 + valacyclovir in combination with continued ICI in patients with non-resectable, stage III/IV NSCLC, refractory or resistant to anti-PD-(L)1. Patients were enrolled in 2 cohorts (C) depending on disease status at enrolment: C1, stable disease or C2, progressive disease. Two doses of CAN-2409 (5x1011vp) were given 5-7w apart via bronchoscopic or percutaneous injection into lung tumor, disease-positive lymph node, or peripheral metastasis, each followed by oral prodrug. Patients were assessed for safety, immunologic biomarkers, and OS. Results: As of 16Jan2024, 73 patients were treated (safety population: ≥1 dose of CAN-2409) and 44 were evaluable per protocol (received 2 doses of CAN-2409+ valacyclovir and 12-week CT scan). Baseline treated pt median age was 67 [43-88] yrs, 44% female, 68% on aPD(L)1 alone and 32% aPD(L)1 + pemetrexed regimen. We observed no dose-limiting toxicities or ≥grade 4 treatment-related AEs. mOS of the evaluable population was estimated as 22.0m (95% CI: 14.3m, NA; median follow up (mFU) time of 18.2m). In C2 (n = 38) mOS was 20.6 (mFU 19.2.m) and in C1 (n = 6) was N.A. (mFU 15.2m). mOS in the safety population (n = 73) was 14.3.m (mFU16.8m). 64% of evaluable patients had systemic clinical response with shrinkage of both injected and uninjected lesions. We found a significant correlation between increases in T cell populations after the second injection of CAN-2409 (circulating memory and effector memory CD4+ and CD8+T cells, CD4+ Ki67+IFNg+ and CD4+granzymeB+ T cells, CD8+granzymeB+Ki67+ T cells, T regulatory cells) and subsequent OS (R2 between 0.181 and 0.354 and p = 0.043 and 0.004). Conclusions: Experimental treatment with CAN-2409+valacyclovir in NSCLC pts following an inadequate response to ICI is well tolerated and results in the induction of a cytotoxic and memory circulating T cell response associated with shrinkage of injected and uninjected lesions and a raised tail of the survival curve. mOS of the evaluable population was estimated as 22.0m, markedly longer than the expected mOS of 11.6-14.5m. Clinical trial information: NCT04495153 .

Abstract Recent advances in the field of immuno‐oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high‐throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi‐marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Introduction Newly-diagnosed multiple myeloma (MM) patients often share tumor genetic abnormalities associated with a high risk of progression and poor survival. We hypothesized that single-cell transcriptomic characterization of the tumor immune microenvironment (TIME) may be combined with tumor-based risk stratification to uncover novel disease biology mechanisms associated with clinical outcomes and improve risk stratification. Methods We performed single-cell RNA sequencing of 361 CD138 negative sorted bone marrow mononuclear cells (BMMCs) samples from 263 MM patients enrolled at time of diagnosis in the Multiple Myeloma Research Foundation CoMMpass study (NCT01454297). Specimens were analyzed at baseline (n=263) across a network of five collaborating academic research centers following assay harmonization. Genetic factors that determine risk were defined as one or more of the following gain- or loss-of-function events derived from baseline genomic sequencing data: del17p14, translocations of the Ig locus with the MAF/A/B or WHSC1/MMSET/NSD2 loci, and gain of chromosome 1q21. Statistical modeling strategies were used to assess single-cell populations or RNA signatures associations with known risk factors or disease progression (FDR<0.05). Results The study generated high-quality single-cell profiles of 731,643 cells from 123 high-risk and 107 standard-risk MM patients based on genetics. Based on distinct transcriptome profiles, BMMCs formed 106 clusters corresponding to 5 major compartments: NK and T cells, B cells, erythrocytes, myeloid cells, and plasma cells. Our preliminary differential abundance analysis comparing high- vs standard-risk patients at baseline uncovered significant differences in the TIME associated with genetic risk. The high-risk group was identified as enriched in effector CD8+, and CD4+ T cells. In contrast, the high-risk group exhibited depletion of naive CD8+ and interferon-associated CD4+ and CD8+ T as compared to the standard-risk group. Within subclusters in the T and NK cells compartment, a higher cytotoxicity signature was observed in high-risk patients, characterized by the expression of granzymes and perforin. Finally, our preliminary survival and progression analysis associated a higher frequency of IDO1-expressing macrophages in worst progression patients, while better outcomes were associated with CD8+ T and B cells expressing androgen response and IL6/STAT3/EMT programs, respectively. Conclusions Current approaches for risk stratification are based on bulk measurements of tumor's genetic or epigenetics features, which do not capture the diversity and dynamics of the TIME. Through single-cell transcriptomics, we were able to capture, in high granularity, the TIME and correlate specific immune cell populations and phenotypes with relapse risk and poor prognostic outcomes. These results suggest that immune subpopulations may be an essential novel aspect for improving current risk stratification models.

Background: We previously reported that treatment with the anti-CD30 antibody-drug conjugate brentuximab vedotin (BV) in combination with the checkpoint inhibitors targeting CTLA-4 and/or PD-1 (ipilimumab (I) and nivolumab (N)) led to high overall response rates (ORR) and complete response (CR) rates in relapsed/refractory (R/R) Hodgkin's lymphoma patients in a Phase 1 ECOG-ACRIN sponsored clinical trial. As previously presented in the Phase 1 component of NCT01896999 (E4412), the ORR for the treatment arms were: BV+I 76%, BV+N 89%, and BV+I+N 82%, with CR rates of 57%, 61%, and 73% across the groups, respectively. This suggested that not all patients who responded derived equal benefit. Moreover, with a median follow-up of 2.24 years, the PFS of 1.1 year, NR, and 2.49 years across the groups suggest that even some patients who achieved CR progressed on or subsequent to treatment. Currently biomarkers have no ability to predict which patients will maximally benefit from these therapies. We investigated blood-based immune biomarkers mechanistically across all cohorts which may explain differential responses and guide future treatment decisions for R/R HL patients. Methods: Peripheral blood plasma for 54 of 61 (89%) patients evaluable for response was collected at up to 4 time points and tested for 92 immuno-oncology soluble analytes with Olink proximity extension assay and for antibody titers to 20 known tumor antigens by ELISA. Matching peripheral blood mononuclear cells (PBMC) were analyzed by CyTOF mass cytometry for major immune cell subsets and marker surface expression, and for T cell receptor diversity by Immunoseq®. Mixed effect linear models were used to identify significantly associated changes (P<0.05) related to treatment longitudinally within groups and to ORR between groups. Results: Analysis of plasma demonstrated durable increase in soluble plasma PD-1 and decreases in CCL17, ANGPT2, MMP12, IL13, and CXCL13 in N-containing regimens, and higher GZMA and CAIX in BV+I (P<0.05). Despite baseline heterogeneity in PBMC composition, we found durable increases in plasmacytoid dendritic cells (pDC) after N-containing treatments, and transient increases in plasmablasts and memory B cells, as well as early decreases in naïve CD4+ T cells and neutrophils across treatments. Treatment with BV+I+N demonstrated late increases in neutrophils, and changes in memory B cell markers. Clinical benefit analyses revealed that elevated soluble CD5, ADA, CXCL13, and CCL17 at baseline or after two treatment cycles were associated with worse ORR (P<0.05), and that a module of co-regulated soluble analytes at baseline, including MUC16, was associated with worse progression free survival (PFS) (P<0.05). NY-ESO-1 autoantibodies were more frequent in non-responders, and the top 10% of expanded TCR clonotypes were increased in responders after one treatment cycle (P<0.05). Conclusion: This data reveals differential immune activation based on treatment modality for patients with R/R HL receiving checkpoint-based regimens in combination with an ADC. Our data highlights potential tumor- and immune-derived predictive and pharmacodynamic biomarker candidates of response and resistance. These novel findings have relevance for R/R HL patients receiving immunotherapy and other immunotherapy combinations such as immuno-chemotherapy platforms. Prospective evaluation of these biomarkers in the Phase II component of this study, a randomized comparison of BV+N vs. BV+N+I which has completed adult accrual, is planned. Figure Legend Clinical responders and non-responder patient samples were analyzed using ELISA (auto antibodies), CyTOF (Cell populations), TCRseq (T cell clonality) and Olink (proteomics). The results showed that pDCs, Neutrophils and B-Plasmablasts increased with specific drug combinations independently of clinical response. While T Cell expansion was associated with clinical response, the increase of auto antibodies against NY-ESO-1 and circulating proteins CD5, ADA, MUC16, CXCL13, CXCL9 and CCL17 were associated with worse prognosis

Abstract Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector‐based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well‐described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

AbstractThe clinical significance of the tumor‐immune interaction in breast cancer is now established, and tumor‐infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple‐negative (estrogen receptor, progesterone receptor, and HER2‐negative) breast cancer and HER2‐positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state‐of‐the‐art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false‐positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in‐depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple‐negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

3533 Background: The BACCI trial (NCT02873195) randomized 133 mCRC pts to C+B+A (investigational) or C+B+placebo. Longer progression free survival (PFS) was observed in the investigational vs placebo arm. To investigate T-cell functional heterogeneity, we performed single-cell proteomic analyses on pts with either long or short PFS and evaluated T-cell function as a prognostic and predictive biomarker. Methods: Isolated CD8+ and CD4+ cells were analyzed at baseline and first restaging from pts with long ( > 6 mo, N = 14) or short ( < 2 mo, N = 13) PFS. Single-cell, functional proteomic analyses were conducted using the IsoLight system (Isoplexis), which assessed secretion of 32 cytokines from an average of 786 cells per sample. The cumulative readout was polyfunctional strength index (PSI), a composite score of frequency and magnitude of secreted cytokines. Cytokines are organized into effector (E), stimulatory, chemoattractive (CA), regulatory, and inflammatory (I) clusters. Differential expression analyses were done using Wilcoxon rank-sum tests. Potential predictive effects were assessed using logistic regressions with interaction between treatment and biomarkers. No multiple comparison control was done due to the exploratory nature of analyses. Results: Baseline CD8+ and CD4+ cells were stimulated ex vivo and single-cell cytokine analyses performed. Prognostic analyses indicated that CD8+ cells from pts with long PFS had ~3-fold higher PSI compared to pts with short PFS (p = 0.005). Further analysis identified that the E (p = 0.005) and CA clusters (p = 0.005) most impacted PSI, significant individual cytokines are listed in the table. Baseline CD8+ cell function was not predictive of outcome. Baseline CD4+ cell function was not prognostic or predictive of outcome. Analysis of CD8+ cells after treatment identified that changes in CA cluster was prognostic of long PFS (p = 0.024). Cytokine changes from CD4+ cells were not prognostic; however, early changes in the CD4+ CA cluster were predictive of outcome (p-int = 0.055). Similarly, early changes in the CD8+ I cluster were predictive of outcome (p-int = 0.073). Conclusions: These results reveal pts with long PFS had more functional CD8+ T-cells with a higher PSI than pts with short PFS. Predictive analyses suggested that early changes in the CD4+ CA and CD8+ I clusters were associated with benefit from immunotherapy. These preliminary results highlight the importance of single-cell functional proteomic analyses. [Table: see text]

Abstract Background Biomarkers for predicting the development of Ulcerative Colitis (UC) and disease-related complications are lacking. Anti-integrin αvβ6 IgG autoantibodies (anti-αvβ6) have been recently described in patients diagnosed with UC. Here, we sought to determine if anti-αvβ6 autoantibodies predate UC development and to study associations between anti-αvβ6 and disease outcomes in newly diagnosed UC patients. Methods In a unique pre-clinical IBD cohort from the PRoteomic Evaluation and Discovery in an IBD Cohort of Tri-service Subjects (PREDICTS), anti-αvβ6 were measured in longitudinal pre-diagnosis serum samples from 82 subjects who later developed UC as well as in 82 matched subjects that did not develop IBD (HC). Sample A was at the time of UC diagnosis, Sample B was at a median of 2 years before Sample A, Sample C was at a median of 4 years before Sample A and Sample D was at a median of 10 years before Sample A. In a distinct, external validation cohort (the Crohn’s and Colitis Canada Genetics Environment Microbial (GEM) Project), we tested samples from 12 subjects who later developed UC and compared those with 49 matched subjects who remained asymptomatic. Further, anti-αvβ6 were measured in 2 incident IBD cohorts (COMPASS, n=55 and OSCCAR, n=104 UC subjects) and associations between anti-αvβ6 and adverse UC-outcomes were defined using Cox proportional-hazards model. Results Anti-αvβ6 were significantly higher in the PREDICTS cohort among individuals who developed UC compared to HC up to 10 years prior to diagnosis (Figure 1A). The anti-αvβ6 seropositivity was 12.2% 10 years before diagnosis and increased to 52.4% at the time of diagnosis in subjects who developed UC compared with 2.7% in controls across the 4 timepoints. Additionally, the predictive performance of anti-αvβ6 autoantibodies as assessed via area under the receiver operator curves (AUROC) with 10-fold cross validation was at least 0.8 up to 10 years before diagnosis (Figure 1B). Elevated levels of anti-αvβ6 in pre-clinical UC samples were further validated in the GEM cohort (Figure 1C). Finally, high anti-αvβ6 were associated with a composite of adverse UC-outcomes including hospitalization, disease extension, colectomy, systemic steroid use and/or escalation to biologic therapy in both incident cohorts (Figure 1D). Conclusion Anti-integrin αvβ6 autoantibodies precede the clinical diagnosis of UC by up to 10 years and are associated with adverse UC-related outcomes.