Impact of Neoadjuvant Immunotherapy on Recurrence-Free Survival in Patients with High-Risk Localized HCC.

Surgical resection for localized hepatocellular carcinoma (HCC) is typically reserved for a minority of patients with favorable tumor features and anatomy. Neoadjuvant immunotherapy can expand the number of patients who are candidates for surgical resection and potentially reduce the chance for recurrence, but its role in HCC not defined. We retrospectively examined the outcomes of patients who underwent surgical resection for HCC at the Johns Hopkins Hospital and compared the clinical outcomes of patients who received neoadjuvant immunotherapy with those who underwent upfront resection. The clinical cohort included a total of 92 patients, 36 of whom received neoadjuvant immune checkpoint inhibitor (ICI)-based treatment. A majority of patients (61.1%) who received neoadjuvant ICI-based therapy were outside of standard resectability criteria and were more likely to have features known to confer risk of disease recurrence, including α-fetoprotein ≥ 400 ng/mL (P = 0.02), tumor diameter ≥ 5 cm (P = 0.001), portal vein invasion (P < 0.001), and multifocality (P < 0.001). Patients who received neoadjuvant immunotherapy had similar rates of margin-negative resection (P = 0.47) and recurrence-free survival (RFS) as those who underwent upfront surgical resection (median RFS 44.8 months compared with 49.3 months, respectively, log-rank P = 0.66). There was a nonsignificant trend toward superior RFS in the subset of patients with a pathologic response (tumor necrosis ≥ 70%) with neoadjuvant immunotherapy. Neoadjuvant ICI-based therapy may allow high-risk patients, including those who are outside traditional resectability criteria, to achieve comparable clinical outcomes with those who undergo upfront resection. SIGNIFICANCE: Surgical resection for localized HCC is typically only reserved for those with solitary tumors without vascular invasion. In this retrospective analysis, we show that neoadjuvant immunotherapy may allow high-risk patients, including those who are outside of standard resection criteria, to undergo successful margin-negative resection and achieve comparable long-term clinical outcomes compared with upfront resection. These findings highlight need for prospective studies on neoadjuvant immunotherapy in HCC.

Integration of Clinical Trial Spatial Multiomics Analysis and Virtual Clinical Trials Enables Immunotherapy Response Prediction and Biomarker Discovery.

Due to the lack of treatment options, there remains a need to advance new therapeutics in hepatocellular carcinoma (HCC). The traditional approach moves from initial molecular discovery through animal models to human trials to advance novel systemic therapies that improve treatment outcomes for patients with cancer. Computational methods that simulate tumors mathematically to describe cellular and molecular interactions are emerging as promising tools to simulate the impact of therapy entirely in silico, potentially greatly accelerating delivery of new therapeutics to patients. To facilitate the design of dosing regimens and identification of potential biomarkers for immunotherapy, we developed a new computational model to track tumor progression at the organ scale while capturing the spatial heterogeneity of the tumor in HCC. This computational model of spatial quantitative systems pharmacology was designed to simulate the effects of combination immunotherapy. The model was initiated using literature-derived parameter values and fitted to the specifics of HCC. Model validation was done through comparison with spatial multiomics data from a neoadjuvant HCC clinical trial combining anti-PD1 immunotherapy and a multitargeted tyrosine kinase inhibitor cabozantinib. Validation using spatial proteomics data from imaging mass cytometry demonstrated that closer proximity between CD8 T cells and macrophages correlated with nonresponse. We also compared the model output with Visium spatial transcriptomics profiling of samples from posttreatment tumor resections in the clinical trial and from another independent study of anti-PD1 monotherapy. Spatial transcriptomics data confirmed simulation results, suggesting the importance of spatial patterns of tumor vasculature and TGFß in tumor and immune cell interactions. Our findings demonstrate that incorporating mathematical modeling and computer simulations with high-throughput spatial multiomics data provides a novel approach for patient outcome prediction and biomarker discovery. Significance: Incorporating mathematical modeling and computer simulations with high-throughput spatial multiomics data provides an effective approach for patient outcome prediction and biomarker discovery.

Scoring PD-L1 Expression in Urothelial Carcinoma: An International Multi-Institutional Study on Comparison of Manual and Artificial Intelligence Measurement Model (AIM-PD-L1) Pathology Assessments.

Assessing programmed death ligand 1 (PD-L1) expression on tumor cells (TCs) using Food and Drug Administration-approved, validated immunoassays can guide the use of immune checkpoint inhibitor (ICI) therapy in cancer treatment. However, substantial interobserver variability has been reported using these immunoassays. Artificial intelligence (AI) has the potential to accurately measure biomarker expression in tissue samples, but its reliability and comparability to standard manual scoring remain to be evaluated. This multinational study sought to compare the %TC scoring of PD-L1 expression in advanced urothelial carcinoma, assessed by either an AI Measurement Model (AIM-PD-L1) or expert pathologists. The concordance among pathologists and between pathologists and AIM-PD-L1 was determined. The positivity rate of ≥ 1%TC PD-L1 was between 20-30% for 8/10 pathologists, and the degree of agreement and scoring distribution for among pathologists and between pathologists and AIM-PD-L1 was similar both scored as a continuous variable or using the pre-defined cutoff. Numerically higher score variation was observed with the 22C3 assay than with the 28-8 assay. A 2-h training module on the 28-8 assay did not significantly impact manual assessment. Cases exhibiting significantly higher variability in the assessment of PD-L1 expression (mean absolute deviation > 10) were found to have patterns of PD-L1 staining that were more challenging to interpret. An improved understanding of sources of manual scoring variability can be applied to PD-L1 expression analysis in the clinical setting. In the future, the application of AI algorithms could serve as a valuable reference guide for pathologists while scoring PD-L1.

Comparing anti-tumor and anti-self immunity in a patient with melanoma receiving immune checkpoint blockade.

BACKGROUND: Tumor regression following immune checkpoint blockade (ICB) is often associated with immune-related adverse events (irAEs), marked by inflammation in non-cancerous tissues. This study was undertaken to investigate the functional relationship between anti-tumor and anti-self immunity, to facilitate irAE management while promoting anti-tumor immunity. METHODS: Multiple biopsies from tumor and inflamed tissues were collected from a patient with melanoma experiencing both tumor regression and irAEs on ICB, who underwent rapid autopsy. Immune cells infiltrating melanoma lesions and inflamed normal tissues were subjected to gene expression profiling with multiplex qRT-PCR for 122 candidate genes. Subsequently, immunohistochemistry was conducted to assess the expression of 14 candidate markers of immune cell subsets and checkpoints. TCR-beta sequencing was used to explore T cell clonal repertoires across specimens. RESULTS: While genes involved in MHC I/II antigen presentation, IFN signaling, innate immunity and immunosuppression were abundantly expressed across specimens, irAE tissues over-expressed certain genes associated with immunosuppression (CSF1R, IL10RA, IL27/EBI3, FOXP3, KLRG1, SOCS1, TGFB1), including those in the COX-2/PGE2 pathway (IL1B, PTGER1/EP1 and PTGER4/EP4). Immunohistochemistry revealed similar proportions of immunosuppressive cell subsets and checkpoint molecules across samples. TCRseq did not indicate common TCR repertoires across tumor and inflammation sites, arguing against shared antigen recognition between anti-tumor and anti-self immunity in this patient. CONCLUSIONS: This comprehensive study of a single patient with melanoma experiencing both tumor regression and irAEs on ICB explores the immune landscape across these tissues, revealing similarities between anti-tumor and anti-self immunity. Further, it highlights expression of the COX-2/PGE2 pathway, which is known to be immunosuppressive and potentially mediates ICB resistance. Ongoing clinical trials of COX-2/PGE2 pathway inhibitors targeting the major COX-2 inducer IL-1B, COX-2 itself, or the PGE2 receptors EP2 and EP4 present new opportunities to promote anti-tumor activity, but may also have the potential to enhance the severity of ICB-induced irAEs.

SREBP-dependent regulation of lipid homeostasis is required for progression and growth of pancreatic ductal adenocarcinoma.

Metabolic reprogramming is a necessary component of oncogenesis and cancer progression that solid tumors undergo when their growth outstrips local nutrient supply. The supply of lipids such as cholesterol and fatty acids is required for continued tumor cell proliferation, and oncogenic mutations stimulate de novo lipogenesis to support tumor growth. Sterol regulatory element-binding protein (SREBP) transcription factors control cellular lipid homeostasis by activating genes required for lipid synthesis and uptake. SREBPs have been implicated in the progression of multiple cancers, including brain, breast, colon, liver, and prostate. However, the role the SREBP pathway and its central regulator SREBP cleavage activating protein (SCAP) in pancreatic ductal adenocarcinoma (PDAC) has not been studied in detail. Here, we demonstrated that pancreas-specific knockout of Scap has no effect on mouse pancreas development or function, allowing for examination of the role for Scap in the murine KPC model of PDAC. Notably, heterozygous loss of Scap prolonged survival in KPC mice, and homozygous loss of Scap impaired PDAC tumor progression. Using subcutaneous and orthotopic xenograft models, we showed that S CAP is required for human PDAC tumor growth. Mechanistically, chemical or genetic inhibition of the SREBP pathway prevented PDAC cell growth under low serum conditions due to a lack of lipid supply. Highlighting the clinical importance of this pathway, the SREBP pathway is broadly required for cancer cell growth, SREBP target genes are upregulated in human PDAC tumors, and increased expression of SREBP targets genes is associated with poor survival in PDAC patients. Collectively, these results demonstrate that SCAP and the SREBP pathway activity are essential for PDAC cell and tumor growth in vitro and in vivo , identifying SCAP as a potential therapeutic target for PDAC. SIGNIFICANCE: Our findings demonstrate that SREBP pathway activation is a critical part of the metabolic reprogramming that occurs in PDAC development and progression. Therefore, targeting the SREBP pathway has significant therapeutic potential.

Entinostat, nivolumab and ipilimumab for women with advanced HER2-negative breast cancer: a phase Ib trial.

We report the results of 24 women, 50% (N = 12) with hormone receptor-positive breast cancer and 50% (N = 12) with advanced triple-negative breast cancer, treated with entinostat + nivolumab + ipilimumab from the dose escalation (N = 6) and expansion cohort (N = 18) of ETCTN-9844 ( NCT02453620 ). The primary endpoint was safety. Secondary endpoints were overall response rate, clinical benefit rate, progression-free survival and change in tumor CD8:FoxP3 ratio. There were no dose-limiting toxicities. Among evaluable participants (N = 20), the overall response rate was 25% (N = 5), with 40% (N = 4) in triple-negative breast cancer and 10% (N = 1) in hormone receptor-positive breast cancer. The clinical benefit rate was 40% (N = 8), and progression-free survival at 6 months was 50%. Exploratory analyses revealed that changes in myeloid cells may contribute to responses; however, no correlation was noted between changes in CD8:FoxP3 ratio, PD-L1 status and tumor mutational burden and response. These findings support further investigation of this treatment in a phase II trial.

Neoadjuvant radioimmunotherapy in pancreatic cancer enhances effector T cell infiltration and shortens their distances to tumor cells.

Radiotherapy is hypothesized to have an immune-modulating effect on the tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) to sensitize it to anti-PD-1 antibody (a-PD-1) treatment. We collected paired pre- and posttreatment specimens from a clinical trial evaluating combination treatment with GVAX vaccine, a-PD-1, and stereotactic body radiation (SBRT) following chemotherapy for locally advanced PDACs (LAPC). With resected PDACs following different neoadjuvant therapies as comparisons, effector cells in PDACs were found to skew toward a more exhausted status in LAPCs following chemotherapy. The combination of GVAX/a-PD-1/SBRT drives TME to favor antitumor immune response including increased densities of GZMB+CD8+ T cells, TH1, and TH17, which are associated with longer survival, however increases immunosuppressive M2-like tumor-associated macrophages (TAMs). Adding SBRT to GVAX/a-PD-1 shortens the distances from PD-1+CD8+ T cells to tumor cells and to PD-L1+ myeloid cells, which portends prolonged survival. These findings have guided the design of next radioimmunotherapy studies by targeting M2-like TAM in PDACs.