Neoadjuvant intratumoral plasmid interleukin-12 electro-gene-transfer and nivolumab in patients with operable locoregionally advanced melanoma.

PURPOSE: Intratumoral (IT) TAVO-EP (tavokinogene telseplasmid delivered by electroporation) results in localized expression of interleukin-12 (IL-12) within the tumor microenvironment (TME). This study evaluated neoadjuvant TAVO-EP combined with intravenous (IV) nivolumab followed by surgery and adjuvant nivolumab in patients with operable locoregionally advanced melanoma. PATIENTS AND METHODS: The neoadjuvant phase comprised up to 3 Χ 4-week cycles where TAVO-EP was given IT on days 1, 8, and 15 (optional) concurrently with 480 mg nivolumab IV on day 8 of each 4-week cycle. Surgery followed, and adjuvant nivolumab was initiated after surgery. The primary endpoint was pathologic complete response (pCR). Secondary endpoints included major pathological response (MPR; pCR or near pCR). RESULTS: Sixteen patients were enrolled and the preoperative radiological response rate was 63%. One patient declined surgery after experiencing a significant clinical response. Among the remaining 15 patients, pCR rate was 60% and MPR was 80%. No patient with MPR has had disease recurrence with a median follow-up from the date of surgery of 15.4 months. At baseline, most patients exhibited low CD8+ TIL, PD-L1 and IFN-γ gene expression signature. There was enhanced immune activation following treatment in the TME and blood including increased immune-related gene expression, CD8+ TIL and proliferating immune cell subsets. CONCLUSIONS: The clinical efficacy of neoadjuvant IT TAVO-EP + nivolumab is promising with 80% of patients achieving an MPR. Evidence of potent immune activation both systemically and within the TME along with a favorable safety profile supports the activity of local IL-12 and anti-PD1 based regimens.

Durability of response to immune checkpoint blockade following treatment discontinuation and efficacy of rechallenge in advanced Merkel cell carcinoma.

BACKGROUND: Advanced Merkel cell carcinoma (MCC) has a high response rate to immune checkpoint blockade (ICB) therapy, but the durability of responses once treatment is discontinued remains unclear. We therefore reviewed the long-term outcomes of advanced patients with MCC who discontinued ICB treatment after achieving favorable initial response. METHODS: We performed a retrospective review of advanced patients with MCC treated at a single high-volume referral center, including all patients who received at least one dose of anti-programmed death receptor 1 (ligand) monotherapy for unresectable or metastatic disease, achieved stable disease (SD) or better, and discontinued treatment for a reason other than disease progression. RESULTS: Of 195 advanced patients with MCC treated with ICB, we identified 45 who met the study criteria. Of these, 21 (46.6%) had a complete response (CR) to initial ICB treatment, 23 (51.1%) a partial response and 1 (2.2%) SD. 25 (55.6%) patients discontinued ICB electively and 20 (44.4%) discontinued due to toxicity. In total, 21 of the 45 patients (46.6%) experienced disease progression at a median of 11.3 months (range 2.1-22.7 months) from ICB cessation. There was a lower rate of progression in patients who achieved CR versus non-CR (23.8% vs 66.7%, p=0.006) and a trend towards a lower rate in those who discontinued electively versus due to toxicity (36.0% vs 60.0%, p=0.14). There was a higher risk for progression in patients with viral positive MCC compared with viral negative MCC (75.0 vs 30.8%, p=0.02). 16 of the 21 patients who experienced progression were retreated subsequently with ICB therapy, including both single-agent rechallenge (12) and escalation to combination ICB (4). 11 of 15 evaluable ICB-retreated patients (73.3%) achieved an objective response. CONCLUSIONS: Patients with advanced MCC have a substantial risk of disease progression following treatment discontinuation despite initial favorable ICB response, particularly in those that achieve less than a CR. Most of these patients maintain sensitivity to retreatment with the same drug class. Virus-positive MCC may be a risk factor for post-discontinuation relapse, which should be validated in future studies.

Tenascin-C in the early lung cancer tumor microenvironment promotes progression through integrin αvß1 and FAK.

Pre-cancerous lung lesions are commonly initiated by activating mutations in the RAS pathway, but do not transition to lung adenocarcinomas (LUAD) without additional oncogenic signals. Here, we show that expression of the extracellular matrix protein Tenascin-C (TNC) is increased in and promotes the earliest stages of LUAD development in oncogenic KRAS-driven lung cancer mouse models and in human LUAD. TNC is initially expressed by fibroblasts and its expression extends to tumor cells as the tumor becomes invasive. Genetic deletion of TNC in the mouse models reduces early tumor burden and high-grade pathology and diminishes tumor cell proliferation, invasion, and focal adhesion kinase (FAK) activity. TNC stimulates cultured LUAD tumor cell proliferation and migration through engagement of αv-containing integrins and subsequent FAK activation. Intringuingly, lung injury causes sustained TNC accumulation in mouse lungs, suggesting injury can induce additional TNC signaling for early tumor cell transition to invasive LUAD. Biospecimens from patients with stage I/II LUAD show TNC in regions of FAK activation and an association of TNC with tumor recurrence after primary tumor resection. These results suggest that exogenous insults that elevate TNC in the lung parenchyma interact with tumor-initiating mutations to drive early LUAD progression and local recurrence.

The Tumor Microbiome as a Predictor of Outcomes in Patients with Metastatic Melanoma Treated with Immune Checkpoint Inhibitors.

Emerging evidence supports the important role of the tumor microbiome in oncogenesis, cancer immune phenotype, cancer progression, and treatment outcomes in many malignancies. In this study, we investigated the metastatic melanoma tumor microbiome and its potential roles in association with clinical outcomes, such as survival, in patients with metastatic disease treated with immune checkpoint inhibitors (ICI). Baseline tumor samples were collected from 71 patients with metastatic melanoma before treatment with ICIs. Bulk RNA sequencing (RNA-seq) was conducted on the formalin-fixed, paraffin-embedded and fresh frozen tumor samples. Durable clinical benefit (primary clinical endpoint) following ICIs was defined as overall survival >24 months and no change to the primary drug regimen (responders). We processed RNA-seq reads to carefully identify exogenous sequences using the {exotic} tool. The age of the 71 patients with metastatic melanoma ranged from 24 to 83 years, 59% were male, and 55% survived >24 months following the initiation of ICI treatment. Exogenous taxa were identified in the tumor RNA-seq, including bacteria, fungi, and viruses. We found differences in gene expression and microbe abundances in immunotherapy-responsive versus nonresponsive tumors. Responders showed significant enrichment of bacteriophages in the phylum Uroviricota, and nonresponders showed enrichment of several bacteria, including Campylobacter jejuni. These microbes correlated with immune-related gene expression signatures. Finally, we found that models for predicting prolonged survival with immunotherapy using both microbe abundances and gene expression outperformed models using either dataset alone. Our findings warrant further investigation and potentially support therapeutic strategies to modify the tumor microbiome in order to improve treatment outcomes with ICIs. SIGNIFICANCE: We analyzed the tumor microbiome and interactions with genes and pathways in metastatic melanoma treated with immunotherapy and identified several microbes associated with immunotherapy response and immune-related gene expression signatures. Machine learning models that combined microbe abundances and gene expression outperformed models using either dataset alone in predicting immunotherapy responses.

Multicellular immune ecotypes within solid tumors predict real-world therapeutic benefits with immune checkpoint inhibitors.

Background: Cancer initiation, progression, and immune evasion depend on the tumor microenvironment (TME). Thus, understanding the TME immune architecture is essential for understanding tumor metastasis and therapy response. This study aimed to create an immune cell states (CSs) atlas using bulk RNA-seq data enriched by eco-type analyses to resolve the complex immune architectures in the TME. Methods: We employed EcoTyper, a machine-learning (ML) framework, to study the real-world prognostic significance of immune CSs and multicellular ecosystems, utilizing molecular data from 1,610 patients with multiple malignancies who underwent immune checkpoint inhibitor (ICI) therapy within the ORIEN Avatar cohort, a well-annotated real-world dataset. Results: Our analysis revealed consistent ICI-specific prognostic TME carcinoma ecotypes (CEs) (including CE1, CE9, CE10) across our pan-cancer dataset, where CE1 being more lymphocyte-deficient and CE10 being more proinflammatory. Also, the analysis of specific immune CSs across different cancers showed consistent CD8+ and CD4+ T cell CS distribution patterns. Furthermore, survival analysis of the ORIEN ICI cohort demonstrated that ecotype CE9 is associated with the most favorable survival outcomes, while CE2 is linked to the least favorable outcomes. Notably, the melanoma-specific prognostic EcoTyper model confirmed that lower predicted risk scores are associated with improved survival and better response to immunotherapy. Finally, de novo discovery of ecotypes in the ORIEN ICI dataset identified Ecotype E3 as significantly associated with poorer survival outcomes. Conclusion: Our findings offer important insights into refining the patient selection process for immunotherapy in real-world practice and guiding the creation of novel therapeutic strategies to target specific ecotypes within the TME.

The Tumor Microbiome Reacts to Hypoxia and Can Influence Response to Radiation Treatment in Colorectal Cancer.

Tumor hypoxia has been shown to predict poor patient outcomes in several cancer types, partially because it reduces radiation's ability to kill cells. We hypothesized that some of the clinical effects of hypoxia could also be due to its impact on the tumor microbiome. Therefore, we examined the RNA sequencing data from the Oncology Research Information Exchange Network database of patients with colorectal cancer treated with radiotherapy. We identified microbial RNAs for each tumor and related them to the hypoxic gene expression scores calculated from host mRNA. Our analysis showed that the hypoxia expression score predicted poor patient outcomes and identified tumors enriched with certain microbes such as Fusobacterium nucleatum. The presence of other microbes, such as Fusobacterium canifelinum, predicted poor patient outcomes, suggesting a potential interaction between hypoxia, the microbiome, and radiation response. To experimentally investigate this concept, we implanted CT26 colorectal cancer cells into immune-competent BALB/c and immune-deficient athymic nude mice. After growth, in which tumors passively acquired microbes from the gastrointestinal tract, we harvested tumors, extracted nucleic acids, and sequenced host and microbial RNAs. We stratified tumors based on their hypoxia score and performed a metatranscriptomic analysis of microbial gene expression. In addition to hypoxia-tropic and -phobic microbial populations, analysis of microbial gene expression at the strain level showed expression differences based on the hypoxia score. Thus, hypoxia gene expression scores seem to associate with different microbial populations and elicit an adaptive transcriptional response in intratumoral microbes, potentially influencing clinical outcomes. SIGNIFICANCE: Tumor hypoxia reduces radiotherapy efficacy. In this study, we explored whether some of the clinical effects of hypoxia could be due to interaction with the tumor microbiome. Hypoxic gene expression scores associated with certain microbes and elicited an adaptive transcriptional response in others that could contribute to poor clinical outcomes.

Patient reported outcomes and patient experiences of immune checkpoint modulators for advanced or recurrent melanoma: a mixed methods study.

PURPOSE: Little is known about late and long-term patient-reported outcomes (PROs) of immune checkpoint modulators (ICMs) outside clinical trials. We conducted a cross-sectional, mixed-methods study to describe long-term PROs among advanced melanoma patients who began standard of care treatment with ICMs at least 1 year previously. METHODS: All participants completed the Functional Assessment of Cancer Therapy-Immune Checkpoint Modulator (FACT-ICM), assessing 46 immune-related side effects on a 5-point Likert scale, and a subset completed individual interviews. Descriptive statistics were computed for quantitative data and applied thematic analysis was used to examine qualitative data. RESULTS: Participants (N = 80) had a mean age of 67 years, and the majority were male (66%), non-Hispanic White (96%), and college graduates (61%). Single-agent nivolumab was the most common first (47%) and current/recent ICM (64%). On the FACT-ICM, 98% of participants reported at least one side effect, and 78% reported moderate or severe side effects. The most common moderate or severe side effects were aching joints (43%) and fatigue (38%). In interviews (n = 20), we identified five themes regarding patients' longer-term experiences after ICMs: lasting fatigue or decline in functioning, minimal side effects, manageable thyroid and pituitary dysfunction, skin conditions can be difficult to manage, and treating the cancer is worth the side effects. CONCLUSIONS: Nearly all patients reported side effects of ICMs at least 1 year after starting treatment. Our findings suggest that ICM side effect screening and management-especially for aching joints and fatigue-are indicated during long-term care of people living with advanced melanoma.

First-in-Human Stage III/IV Melanoma Clinical Trial of Immune Priming Agent IFx-Hu2.0.

IFx-Hu2.0 was designed to encode part of the Emm55 protein contained within a plasmid in a formulation intended for transfection into mammalian cells. IFx-Hu2.0 promotes both adaptive and innate immune responses in animal studies. Furthermore, previous studies have demonstrated safety/efficacy in equine, canine, and murine species. We present the first-in-human study of IFx-Hu2.0, administered by intralesional injection into melanoma tumors of seven patients with stage III/IV unresectable melanoma. No dose-limiting toxicities attributable to IFx-Hu2.0 were observed. Grade 1/2 injection site reactions were observed in five of seven patients. IgG and IgM responses to Emm55 peptides and known melanoma antigens were seen in the peripheral blood, suggesting that IFx-Hu2.0 acts as an individualized "in situ vaccine." Three of four patients previously refractory to anti-PD1 experienced clinical benefit upon subsequent anti-PD1-based treatment. Therefore, this approach is feasible, and clinical/correlative outcomes warrant further investigation for treating patients with metastatic melanoma with an immune priming agent.

Jagged2 targeting in lung cancer activates anti-tumor immunity via Notch-induced functional reprogramming of tumor-associated macrophages.

Signaling through Notch receptors intrinsically regulates tumor cell development and growth. Here, we studied the role of the Notch ligand Jagged2 on immune evasion in non-small cell lung cancer (NSCLC). Higher expression of JAG2 in NSCLC negatively correlated with survival. In NSCLC pre-clinical models, deletion of Jag2, but not Jag1, in cancer cells attenuated tumor growth and activated protective anti-tumor T cell responses. Jag2-/- lung tumors exhibited higher frequencies of macrophages that expressed immunostimulatory mediators and triggered T cell-dependent anti-tumor immunity. Mechanistically, Jag2 ablation promoted Nr4a-mediated induction of Notch ligands DLL1/4 on cancer cells. DLL1/4-initiated Notch1/2 signaling in macrophages induced the expression of transcription factor IRF4 and macrophage immunostimulatory functionality. IRF4 expression was required for the anti-tumor effects of Jag2 deletion in lung tumors. Antibody targeting of Jagged2 inhibited tumor growth and activated IRF4-driven macrophage-mediated anti-tumor immunity. Thus, Jagged2 orchestrates immunosuppressive systems in NSCLC that can be overcome to incite macrophage-mediated anti-tumor immunity.

Treatment of Stage III Resectable Melanoma-Adjuvant and Neoadjuvant Approaches.

ABSTRACT: Patients with stage III resectable melanoma carry a high risk of melanoma recurrence that ranges from approximately 40% to 90% at 5 years following surgical management alone. Postoperative systemic adjuvant therapy targets residual micrometastatic disease that could be the source of future recurrence and death from melanoma. Randomized phase III adjuvant trials reported significant improvements in overall survival with high-dose interferon α in 2 of 3 studies (compared with observation and GMK ganglioside vaccine) and with anti-cytotoxic T-lymphocyte antigen 4 ipilimumab at 10 mg/kg compared with placebo and ipilimumab 3 mg/kg compared with high-dose interferon α. In the modern era, more recent phase III trials demonstrated significant recurrence-free survival improvements with anti-programmed cell death protein 1, pembrolizumab, and BRAF-MEK inhibitor combination dabrafenib-trametinib (for BRAF mutant melanoma) versus placebo. Furthermore, anti-programmed cell death protein 1, nivolumab and pembrolizumab have both been shown to significantly improve recurrence-free survival as compared with ipilimumab 10 mg/kg. For melanoma patients with clinically or radiologically detectable locoregionally advanced disease, emerging data support an important role for preoperative systemic neoadjuvant therapy. Importantly, a recent cooperative group trial (S1801) reported superior event-free survival rates with neoadjuvant versus adjuvant therapy. Collectively, current data from neoadjuvant immunotherapy and targeted therapy trials support a future change in clinical practice in favor of neoadjuvant therapy for eligible melanoma patients.

Comparing the rate of immunotherapy treatment change due to toxicity by sex.

BACKGROUND: Immuno-oncology therapy (IO) is associated with a variety of treatment-related toxicities. However, the impact of toxicity on the treatment discontinuation rate between males and females is unknown. We hypothesized that immune-related adverse events would lead to more frequent treatment changes in females since autoimmune diseases occur more frequently in females. AIMS: Our aim was to determine if there was a difference in the rate of immunotherapy treatment change due to toxicity between males and females. METHODS AND RESULTS: The Oncology Research Information Exchange Network Avatar Database collected clinical data from 10 United States cancer centers. Of 1035 patients receiving IO, 447 were analyzed, excluding those who did not have documentation noting if a patient changed treatment (n = 573). Fifteen patients with unknown or gender-specific cancer were excluded. All cancer types and stages were included. The primary endpoint was documented treatment change due to toxicity. Four hundred and forty-seven patients (281 males and 166 females) received IO treatment. The most common cancers treated were kidney, skin, and lung for 99, 84, and 54 patients, respectively. Females had a shorter IO course than males (median 3.7 vs. 5.1 months, respectively, p = .02). Fifty-four patients changed treatment due to toxicity. There was no significant difference between females and males on chi-square test (11.4% vs. 12.5%, respectively, p = 0.75) and multivariable logistic regression (OR 0.924, 95% CI 0.453-1.885, p = .827). Significantly more patients with chronic obstructive pulmonary disease (COPD) changed therapy due to toxicity (OR 2.491, 95% CI 1.025-6.054, p = .044). CONCLUSION: Females received a shorter course of IO than males. However, there was no significant difference in the treatment discontinuation rate due to toxicity between males and females receiving IO. Toxicity-related treatment change was associated with COPD.

A Bioinformatics Tool for Identifying Intratumoral Microbes from the ORIEN Dataset.

Evidence supports significant interactions among microbes, immune cells, and tumor cells in at least 10%-20% of human cancers, emphasizing the importance of further investigating these complex relationships. However, the implications and significance of tumor-related microbes remain largely unknown. Studies have demonstrated the critical roles of host microbes in cancer prevention and treatment responses. Understanding interactions between host microbes and cancer can drive cancer diagnosis and microbial therapeutics (bugs as drugs). Computational identification of cancer-specific microbes and their associations is still challenging due to the high dimensionality and high sparsity of intratumoral microbiome data, which requires large datasets containing sufficient event observations to identify relationships, and the interactions within microbial communities, the heterogeneity in microbial composition, and other confounding effects that can lead to spurious associations. To solve these issues, we present a bioinformatics tool, microbial graph attention (MEGA), to identify the microbes most strongly associated with 12 cancer types. We demonstrate its utility on a dataset from a consortium of nine cancer centers in the Oncology Research Information Exchange Network. This package has three unique features: species-sample relations are represented in a heterogeneous graph and learned by a graph attention network; it incorporates metabolic and phylogenetic information to reflect intricate relationships within microbial communities; and it provides multiple functionalities for association interpretations and visualizations. We analyzed 2,704 tumor RNA sequencing samples and MEGA interpreted the tissue-resident microbial signatures of each of 12 cancer types. MEGA can effectively identify cancer-associated microbial signatures and refine their interactions with tumors. SIGNIFICANCE: Studying the tumor microbiome in high-throughput sequencing data is challenging because of the extremely sparse data matrices, heterogeneity, and high likelihood of contamination. We present a new deep learning tool, MEGA, to refine the organisms that interact with tumors.

The T Cell Immunoscore as a Reference for Biomarker Development Utilizing Real-World Data from Patients with Advanced Malignancies Treated with Immune Checkpoint Inhibitors.

BACKGROUND: We aimed to determine the prognostic value of an immunoscore reflecting CD3+ and CD8+ T cell density estimated from real-world transcriptomic data of a patient cohort with advanced malignancies treated with immune checkpoint inhibitors (ICIs) in an effort to validate a reference for future machine learning-based biomarker development. METHODS: Transcriptomic data was collected under the Total Cancer Care Protocol (NCT03977402) Avatar® project. The real-world immunoscore for each patient was calculated based on the estimated densities of tumor CD3+ and CD8+ T cells utilizing CIBERSORTx and the LM22 gene signature matrix. Then, the immunoscore association with overall survival (OS) was estimated using Cox regression and analyzed using Kaplan-Meier curves. The OS predictions were assessed using Harrell's concordance index (C-index). The Youden index was used to identify the optimal cut-off point. Statistical significance was assessed using the log-rank test. RESULTS: Our study encompassed 522 patients with four cancer types. The median duration to death was 10.5 months for the 275 participants who encountered an event. For the entire cohort, the results demonstrated that transcriptomics-based immunoscore could significantly predict patients at risk of death (p-value < 0.001). Notably, patients with an intermediate-high immunoscore achieved better OS than those with a low immunoscore. In subgroup analysis, the prediction of OS was significant for melanoma and head and neck cancer patients but did not reach significance in the non-small cell lung cancer or renal cell carcinoma cohorts. CONCLUSIONS: Calculating CD3+ and CD8+ T cell immunoscore using real-world transcriptomic data represents a promising signature for estimating OS with ICIs and can be used as a reference for future machine learning-based biomarker development.

Translation of AI into oncology clinical practice.

Artificial intelligence (AI) is a transformative technology that is capturing popular imagination and can revolutionize biomedicine. AI and machine learning (ML) algorithms have the potential to break through existing barriers in oncology research and practice such as automating workflow processes, personalizing care, and reducing healthcare disparities. Emerging applications of AI/ML in the literature include screening and early detection of cancer, disease diagnosis, response prediction, prognosis, and accelerated drug discovery. Despite this excitement, only few AI/ML models have been properly validated and fewer have become regulated products for routine clinical use. In this review, we highlight the main challenges impeding AI/ML clinical translation. We present different clinical use cases from the domains of radiology, radiation oncology, immunotherapy, and drug discovery in oncology. We dissect the unique challenges and opportunities associated with each of these cases. Finally, we summarize the general requirements for successful AI/ML implementation in the clinic, highlighting specific examples and points of emphasis including the importance of multidisciplinary collaboration of stakeholders, role of domain experts in AI augmentation, transparency of AI/ML models, and the establishment of a comprehensive quality assurance program to mitigate risks of training bias and data drifts, all culminating toward safer and more beneficial AI/ML applications in oncology labs and clinics.

Clinical updates in neoadjuvant immunotherapy for melanoma before surgery.

INTRODUCTION: Locoregionally advanced melanoma represents a large group of high-risk melanoma patients at presentation and poses major challenges in relation to management and the risks of relapse and death. AREAS COVERED: Melanoma systemic therapy has undergone substantial advancements with the advent of immune checkpoint inhibitors and molecularly targeted therapies, which have been translated to the neoadjuvant setting for the management of locoregionally advanced disease. Notably, PD1 blockade as monotherapy, in combination with CTLA4 blockade or LAG3 inhibition, has demonstrated significant progress in reducing the risk of relapse and mortality, attributed to high pathologic response rates. Likewise, BRAF-MEK inhibition for BRAF mutant melanoma has yielded comparable outcomes, albeit with lower response durability than immunotherapy. Localized intralesional therapies such as Talimogene laherparepvec (T-VEC) and Tavokinogene Telseplasmid (TAVO) electro-gene-transfer combined with anti-PD1 have demonstrated favorable pathologic responses and increased immune activation. Most importantly, the S1801 randomized trial has demonstrated for the first time the advantage of the neoadjuvant approach over standard surgery followed by adjuvant therapy. EXPERT OPINION: Current evidence supports neoadjuvant therapy as a standard of care for locoregionally advanced melanoma. Ongoing research will define the optimal regimens and the biomarkers of therapeutic predictive and prognostic value.

Adjuvant Therapy for High-Risk Melanoma: An In-Depth Examination of the State of the Field.

The consideration of systemic adjuvant therapy is recommended for patients with stage IIB-IV melanoma who have undergone surgical resection due to a heightened risk of experiencing melanoma relapse and mortality from melanoma. Adjuvant therapy options tested over the past three decades include high-dose interferon-α, immune checkpoint inhibitors (pembrolizumab, nivolumab), targeted therapy (dabrafenib-trametinib for BRAF mutant melanoma), radiotherapy and chemotherapy. Most of these therapies have been demonstrated to enhance relapse-free survival (RFS) but with limited to no impact on overall survival (OS), as reported in randomized trials. In contemporary clinical practice, the adjuvant treatment approach for surgically resected stage III-IV melanoma has undergone a notable shift towards the utilization of nivolumab, pembrolizumab, and BRAF-MEK inhibitors, such as dabrafenib plus trametinib (specifically for BRAF mutant melanoma) due to the significant enhancements in RFS observed with these treatments. Pembrolizumab has obtained regulatory approval in the United States to treat resected stage IIB-IIC melanoma, while nivolumab is currently under review for the same indication. This review comprehensively analyzes completed phase III adjuvant therapy trials in adjuvant therapy. Additionally, it provides a summary of ongoing trials and an overview of the main challenges and future directions with adjuvant therapy.

Cetuximab for Immunotherapy-Refractory/Ineligible Cutaneous Squamous Cell Carcinoma.

Anti-PD1 therapy demonstrated impressive, prolonged responses in advanced cutaneous squamous cell carcinoma (CSCC). Therapy for ICI-refractory/ineligible disease remains unclear. We performed a retrospective analysis in locally-advanced/metastatic CSCC using cetuximab across three cohorts: immediately after ICI failure (A), not immediately following ICI failure (B), or without prior ICI (C). The primary endpoint was the overall response rate (ORR). Secondary endpoints included disease-control rate (DCR), progression-free survival (PFS), overall survival (OS), time-to-response (TTR) and toxicity. Twenty-three patients were included. In cohort A (n = 11), the ORR was 64% and DCR was 91%, with six ongoing responses at data cutoff. In cohort B (n = 2), all patients had progression as the best response. At a median follow-up of 21 months for A and B, TTR and PFS were 2.0 and 17.3 months, respectively. The median OS was not reached. In cohort C (n = 10), the ORR and DCR were 80%, including five ongoing responses at the data cutoff. At a median follow-up of 22.4 months, the TTR, PFS and OS were 2.5, 7.3 and 23.1 months, respectively. Cetuximab was well tolerated in all cohorts. In summary, cetuximab is effective in patients with failure/contraindications to ICI. Cetuximab immediately after ICI failure yielded particularly fast, durable responses. If confirmed, this could be the preferred therapy following ICI failure.

PATH-SURVEYOR: pathway level survival enquiry for immuno-oncology and drug repurposing.

Pathway-level survival analysis offers the opportunity to examine molecular pathways and immune signatures that influence patient outcomes. However, available survival analysis algorithms are limited in pathway-level function and lack a streamlined analytical process. Here we present a comprehensive pathway-level survival analysis suite, PATH-SURVEYOR, which includes a Shiny user interface with extensive features for systematic exploration of pathways and covariates in a Cox proportional-hazard model. Moreover, our framework offers an integrative strategy for performing Hazard Ratio ranked Gene Set Enrichment Analysis and pathway clustering. As an example, we applied our tool in a combined cohort of melanoma patients treated with checkpoint inhibition (ICI) and identified several immune populations and biomarkers predictive of ICI efficacy. We also analyzed gene expression data of pediatric acute myeloid leukemia (AML) and performed an inverse association of drug targets with the patient's clinical endpoint. Our analysis derived several drug targets in high-risk KMT2A-fusion-positive patients, which were then validated in AML cell lines in the Genomics of Drug Sensitivity database. Altogether, the tool offers a comprehensive suite for pathway-level survival analysis and a user interface for exploring drug targets, molecular features, and immune populations at different resolutions.

The tumor microbiome as a predictor of outcomes in patients with metastatic melanoma treated with immune checkpoint inhibitors.

Emerging evidence supports the important role of the tumor microbiome in oncogenesis, cancer immune phenotype, cancer progression, and treatment outcomes in many malignancies. In this study, we investigated the metastatic melanoma tumor microbiome and potential roles in association with clinical outcomes, such as survival, in patients with metastatic disease treated with immune checkpoint inhibitors (ICIs). Baseline tumor samples were collected from 71 patients with metastatic melanoma before treatment with ICIs. Bulk RNA-seq was conducted on the formalin-fixed paraffin-embedded (FFPE) tumor samples. Durable clinical benefit (primary clinical endpoint) following ICIs was defined as overall survival ≥24 months and no change to the primary drug regimen (responders). We processed RNA-seq reads to carefully identify exogenous sequences using the {exotic} tool. The 71 patients with metastatic melanoma ranged in age from 24 to 83 years, 59% were male, and 55% survived >24 months following the initiation of ICI treatment. Exogenous taxa were identified in the tumor RNA-seq, including bacteria, fungi, and viruses. We found differences in gene expression and microbe abundances in immunotherapy responsive versus non-responsive tumors. Responders showed significant enrichment of several microbes including Fusobacterium nucleatum, and non-responders showed enrichment of fungi, as well as several bacteria. These microbes correlated with immune-related gene expression signatures. Finally, we found that models for predicting prolonged survival with immunotherapy using both microbe abundances and gene expression outperformed models using either dataset alone. Our findings warrant further investigation and potentially support therapeutic strategies to modify the tumor microbiome in order to improve treatment outcomes with ICIs.

A bioinformatics tool for identifying intratumoral microbes from the ORIEN dataset.

Evidence supports significant interactions among microbes, immune cells, and tumor cells in at least 10-20% of human cancers, emphasizing the importance of further investigating these complex relationships. However, the implications and significance of tumor-related microbes remain largely unknown. Studies have demonstrated the critical roles of host microbes in cancer prevention and treatment responses. Understanding interactions between host microbes and cancer can drive cancer diagnosis and microbial therapeutics (bugs as drugs). Computational identification of cancer-specific microbes and their associations is still challenging due to the high dimensionality and high sparsity of intratumoral microbiome data, which requires large datasets containing sufficient event observations to identify relationships, and the interactions within microbial communities, the heterogeneity in microbial composition, and other confounding effects that can lead to spurious associations. To solve these issues, we present a bioinformatics tool, MEGA, to identify the microbes most strongly associated with 12 cancer types. We demonstrate its utility on a dataset from a consortium of 9 cancer centers in the Oncology Research Information Exchange Network (ORIEN). This package has 3 unique features: species-sample relations are represented in a heterogeneous graph and learned by a graph attention network; it incorporates metabolic and phylogenetic information to reflect intricate relationships within microbial communities; and it provides multiple functionalities for association interpretations and visualizations. We analyzed 2704 tumor RNA-seq samples and MEGA interpreted the tissue-resident microbial signatures of each of 12 cancer types. MEGA can effectively identify cancer-associated microbial signatures and refine their interactions with tumors.