Clinical Models to Define Response and Survival With Anti-PD-1 Antibodies Alone or Combined With Ipilimumab in Metastatic Melanoma

Early versus late response to PD-1-based immunotherapy in metastatic melanoma

BACKGROUND

Immune checkpoint inhibition (ICI) currently is the most effective treatment to induce durable responses in metastatic melanoma. The aims of this study are the characterization of patients with early, late and non-response to ICI and analysis of survival outcomes in a real-world patient cohort.

METHODS

Patients who received PD-1-based immunotherapy for non-resectable stage-IV melanoma in any therapy line were selected from the prospective multicenter real-world DeCOG study ADOREG-TRIM (NCT05750511). Patients showing complete (CR) or partial (PR) response already during the first 3 months of treatment (Early Responders, EarlyR) were compared to patients showing CR/PR at a later time (Late Responders, LateR), a stable disease (SD) and to patients showing progressive disease (Non-Responders, NonR).

RESULTS

Of 522 patients, 8.2 % were EarlyR (n = 43), 19.0 % were LateR (n = 99), 37.0 % had a SD (n = 193) and 35.8 % were NonR (n = 187). EarlyR, LateR and SD patients had comparable baseline characteristics. Multivariate logbinomial regression analyses adjusted for age and sex revealed positive tumor PD-L1 (RR=1.99, 95 %-CI=1.14-3.46, p = 0.015), and normal serum CRP (RR=1.59, 95 %-CI=0.93-2.70, p = 0.036) as independently associated with the achievement of an early response compared to NonR. The median progression-free and overall survival was 46.0 months (95 % CI 19.1; NR) and 47.8 months (95 %-CI 36.9; NR) for EarlyR, NR (95 %-CI NR; NR) for LateR, 8.1 months (7.0; 10.4) and 35.4 months (29.2; NR) for SD, and 2.0 months (95 %-CI 1.9; 2.1) and 6.1 months (95 %-CI 4.6; 8.8) for NonR patients.

CONCLUSION

Less than 10 % of metastatic melanoma patients achieved an early response during the first 3 months of PD-1-based immunotherapy. Early responders were not superior to late responders in terms of response durability and survival.

Immunotherapy revolutionizing brain metastatic cancer treatment: personalized strategies for transformative outcomes

Brain metastatic cancer poses a significant clinical challenge, with limited treatment options and poor prognosis for patients. In recent years, immunotherapy has emerged as a promising strategy for addressing brain metastases, offering distinct advantages over conventional treatments. This review explores the evolving landscape of tumor immunotherapy in the context of brain metastatic cancer, focusing on the intricate interplay between the tumor microenvironment (TME) and immunotherapeutic approaches. By elucidating the complex interactions within the TME, including the role of immune cells, cytokines, and extracellular matrix components, this review highlights the potential of immunotherapy to reshape the treatment paradigm for brain metastases. Leveraging immune checkpoint inhibitors, cellular immunotherapies, and personalized treatment strategies, immunotherapy holds promise in overcoming the challenges posed by the blood-brain barrier and immunosuppressive microenvironment of brain metastases. Through a comprehensive analysis of current research findings and future directions, this review underscores the transformative impact of immunotherapy on the management of brain metastatic cancer, offering new insights and opportunities for personalized and precise therapeutic interventions.

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

AIM

The objective of this study was to evaluate whether patient biological sex influences treatment outcomes in patients with metastatic melanoma (MM) undergoing first-line immune checkpoint inhibitor (ICI) therapy.

METHODS

The Danish Metastatic Melanoma Database (DAMMED) was employed to identify patients who underwent first-line ICI therapy for MM in Denmark from 2013 to 2021. Excluding adjuvant treatment, uveal and mucosal histological subtypes, the study conducted univariable and multivariable analyses to evaluate the influence of patient sex in survival analyses. Further, landmark survival of this real-world national cohort was described for progression free survival (PFS), overall survival (OS) and melanoma-specific survival (MSS).

RESULTS

The analysis encompassed a cohort of 1378 patients with MM. Compared to male sex, females had significantly improved OS (p = 0.003) when tested in univariable testing. Multivariable analyses, controlling for age, performance status, lactate dehydrogenase level, BRAF status, M-stage, and number of metastatic sites revealed significant favourable outcomes associated with female sex irrespective of the considered survival metrics (pPFS = 0.014, pOS = 0.002, and pMSS = 0.03). The observed five-year OS rates of the entire cohort were 47% and 38%, while melanoma-specific survival were 50% and 45% for female and male, respectively.

CONCLUSION

In this nationwide cohort of patients with MM undergoing first-line ICI treatment females exhibited superior treatment outcomes compared to males. Sex was identified as an independent predictive variable for treatment outcomes, irrespective of the chosen outcome measures considered. Our analyses are not able to conclude whether the differences in outcome is attributable to differences in biology or to treatment strategy.

Primary Tumor Characteristics as Biomarkers of Immunotherapy Response in Advanced Melanoma: A Retrospective Cohort Study

Identifying patients likely to benefit from immune checkpoint inhibitor (ICI) treatment remains a crucial goal for melanoma. The objective of this study is to assess the association between primary tumor features and immunotherapy response and survival in advanced melanoma patients. In this single-center retrospective cohort study, disease characteristics, response to immunotherapy, PFS, and OS were assessed among melanoma patients (excluding mucosal and uveal primaries) treated with ICI. Among 447 patients, 300 (67.1%) received anti-PD-1 monotherapy and 147 (32.9%) received ipilimumab/nivolumab. A total of 338 (75.6%) had cutaneous melanoma, 29 (6.5%) had acral melanoma, and 80 (17.9%) had melanoma of unknown primary. Ulceration and stage at initial presentation were associated with inferior outcomes on univariate analysis. However, on multivariate analysis, this result was not observed, but cutaneous melanoma and each of its subtypes (superficial spreading, nodular, other, unknown) were positively associated with response, longer PFS, and longer OS. Metastatic stage (M1c, M1d) at presentation (OR = 1.8, p < 0.05) and BRAFV600E mutation status (OR = 1.6, p < 0.001) were associated with shorter PFS. This study is limited by its retrospective and single-center design. Cutaneous melanoma and its subtypes were significantly associated with response, PFS, and OS compared with acral or unknown primary melanoma.

Imaging response to immune checkpoint inhibitors in patients with advanced melanoma: a retrospective observational cohort study

Background

The association between objective imaging response and first line immune checkpoint inhibitor (ICI) therapy regimes in advanced melanoma remains uncharacterized in routine practice.

Methods

We conducted a multi-center retrospective cohort analysis of advanced melanoma patients receiving first line ICI therapy from August 2013-May 2020 in Alberta, Canada. The primary outcome was likelihood of RECIST v1.1 assessed objective imaging response between patients receiving anti-programmed cell death protein 1 (anti-PD1) monotherapy and those receiving combination ipilimumab-nivolumab. Secondary outcomes were identification of baseline characteristics associated with non-response and the association of imaging response with overall survival (OS) and time to next treatment (TTNT).

Results

198 patients were included, 41/198 (20.7%) had complete response, 86/198 (43.4%) had partial response, 23/198 (11.6%) had stable disease, and 48/198 (24.2%) had progressive disease. Median OS was not reached (NR) (95% CI 49.0-NR) months for complete responders, NR (95%CI 52.9-NR) months for partial responders, 33.7 (95%CI 15.8-NR) months for stable disease, and 6.4 (95%CI 5.2-10.1) months for progressive disease (log-rank p<0.001). Likelihood of objective imaging response remained similar between anti-PD1 monotherapy and ipilimumab-nivolumab groups (OR 1.95 95%CI 0.85-4.63, p=0.121). Elevated LDH level (OR 0.46; 95%CI 0.21-0.98, p=0.043), mucosal primary site (OR 0.14; 95%CI 0.03-0.48, p=0.003), and BRAF V600E mutation status (OR 0.31; 95%CI 0.13-0.72, p=0.007) were associated with decreased likelihood of response.

Conclusion

No significant difference in likelihood of imaging response between anti-PD1 monotherapy and combination ipilimumab-nivolumab was observed. Elevated LDH level, mucosal primary site, and BRAF V600E mutation status were associated with decreased likelihood of response. Given that pivotal clinical trials of ipilimumab-nivolumab did not formally compare ipilimumab-nivolumab with nivolumab monotherapy, this work adds context to differences in outcomes when these agents are used. These results may inform treatment selection, and aid in counseling of patients treated with first-line ICI therapy in routine clinical practice settings.

Machine learning in the prediction of immunotherapy response and prognosis of melanoma: a systematic review and meta-analysis

Background

The emergence of immunotherapy has changed the treatment modality for melanoma and prolonged the survival of many patients. However, a handful of patients remain unresponsive to immunotherapy and effective tools for early identification of this patient population are still lacking. Researchers have developed machine learning algorithms for predicting immunotherapy response in melanoma, but their predictive accuracy has been inconsistent. Therefore, the present systematic review and meta-analysis was performed to comprehensively evaluate the predictive accuracy of machine learning in melanoma response to immunotherapy.

Methods

Relevant studies were searched in PubMed, Web of Sciences, Cochrane Library, and Embase from their inception to July 30, 2022. The risk of bias and applicability of the included studies were assessed using the Prediction Model Risk of Bias Assessment Tool (PROBAST). Meta-analysis was performed on R4.2.0.

Results

A total of 36 studies consisting of 30 cohort studies and 6 case-control studies were included. These studies were mainly published between 2019 and 2022 and encompassed 75 models. The outcome measures of this study were progression-free survival (PFS), overall survival (OS), and treatment response. The pooled c-index was 0.728 (95%CI: 0.629-0.828) for PFS in the training set, 0.760 (95%CI: 0.728-0.792) and 0.819 (95%CI: 0.757-0.880) for treatment response in the training and validation sets, respectively, and 0.746 (95%CI: 0.721-0.771) and 0.700 (95%CI: 0.677-0.724) for OS in the training and validation sets, respectively.

Conclusion

Machine learning has considerable predictive accuracy in melanoma immunotherapy response and prognosis, especially in the former. However, due to the lack of external validation and the scarcity of certain types of models, further studies are warranted.

A prediction model for response to immune checkpoint inhibition in advanced melanoma

Predicting who will benefit from treatment with immune checkpoint inhibition (ICI) in patients with advanced melanoma is challenging. We developed a multivariable prediction model for response to ICI, using routinely available clinical data including primary melanoma characteristics. We used a population-based cohort of 3525 patients with advanced cutaneous melanoma treated with anti-PD-1-based therapy. Our prediction model for predicting response within 6 months after ICI initiation was internally validated with bootstrap resampling. Performance evaluation included calibration, discrimination and internal-external cross-validation. Included patients received anti-PD-1 monotherapy (n = 2366) or ipilimumab plus nivolumab (n = 1159) in any treatment line. The model included serum lactate dehydrogenase, World Health Organization performance score, type and line of ICI, disease stage and time to first distant recurrence-all at start of ICI-, and location and type of primary melanoma, the presence of satellites and/or in-transit metastases at primary diagnosis and sex. The over-optimism adjusted area under the receiver operating characteristic was 0.66 (95% CI: 0.64-0.66). The range of predicted response probabilities was 7%-81%. Based on these probabilities, patients were categorized into quartiles. Compared to the lowest response quartile, patients in the highest quartile had a significantly longer median progression-free survival (20.0 vs 2.8 months; P < .001) and median overall survival (62.0 vs 8.0 months; P < .001). Our prediction model, based on routinely available clinical variables and primary melanoma characteristics, predicts response to ICI in patients with advanced melanoma and discriminates well between treated patients with a very good and very poor prognosis.

From algorithms to action: improving patient care requires causality

In cancer research there is much interest in building and validating outcome prediction models to support treatment decisions. However, because most outcome prediction models are developed and validated without regard to the causal aspects of treatment decision making, many published outcome prediction models may cause harm when used for decision making, despite being found accurate in validation studies. Guidelines on prediction model validation and the checklist for risk model endorsement by the American Joint Committee on Cancer do not protect against prediction models that are accurate during development and validation but harmful when used for decision making. We explain why this is the case and how to build and validate models that are useful for decision making.

Prediction of early recovery of graft function after living donor liver transplantation in children

For end-stage liver disease in children, living donor liver transplantation (LDLT) is often the important standard curative treatment. However, there is a lack of research on early recovery of graft function after pediatric LDLT. This is a single-center, ambispective cohort study. We collected the demographic and clinicopathological data of donors and recipients, and determined the risk factors of postoperative delayed recovery of hepatic function (DRHF) by univariate and multivariate Logistic analyses. 181 cases were included in the retrospective cohort and 50 cases in the prospective cohort. The incidence of DRHF after LDLT in children was 29.4%, and DRHF could well evaluate the early recovery of graft function after LDLT. Through Logistic analyses and AIC score, preoperative liver function of donors, ischemia duration level of the liver graft, Ln (Cr of recipients before operation) and Ln (TB of recipients on the 3rd day after operation) were predictive indicators for DRHF after LDLT in children. Using the above factors, we constructed a predictive model to evaluate the incidence of postoperative DRHF. Self-verification and prospective internal verification showed that this prediction model had good accuracy and clinical applicability. In conclusion, we pointed many risk factors for early delayed recovery of graft function after LDLT in children, and developed a visual and personalized predictive model for them, offering valuable insights for clinical management.

Stroma-infiltrating T cell spatiotypes define immunotherapy outcomes in adolescent and young adult patients with melanoma

The biological underpinnings of therapeutic resistance to immune checkpoint inhibitors (ICI) in adolescent and young adult (AYA) melanoma patients are incompletely understood. Here, we characterize the immunogenomic profile and spatial architecture of the tumor microenvironment (TME) in AYA (aged ≤ 30 years) and older adult (aged 31-84 years) patients with melanoma, to determine the AYA-specific features associated with ICI treatment outcomes. We identify two ICI-resistant spatiotypes in AYA patients with melanoma showing stroma-infiltrating lymphocytes (SILs) that are distinct from the adult TME. The SILhigh subtype was enriched in regulatory T cells in the peritumoral space and showed upregulated expression of immune checkpoint molecules, while the SILlow subtype showed a lack of immune activation. We establish a young immunosuppressive melanoma score that can predict ICI responsiveness in AYA patients and propose personalized therapeutic strategies for the ICI-resistant subgroups. These findings highlight the distinct immunogenomic profile of AYA patients, and individualized TME features in ICI-resistant AYA melanoma that require patient-specific treatment strategies.

Immunotherapy in melanoma: Can we predict response to treatment with circulating biomarkers?

Melanoma is the most aggressive form of skin cancer, representing approximately 4% of all cutaneous neoplasms and accounting for up to 80% of deaths. Advanced stages of melanoma involve metastatic processes and are associated with high mortality and morbidity, mainly due to the rapid dissemination and heterogeneous responses to current therapies, including immunotherapy. Immune checkpoint inhibitors (ICIs) are currently used in the treatment of metastatic melanoma (MM) and despite being linked to an increase in patient survival, a high percentage of them still do not benefit from it. Accordingly, the number of therapeutic regimens for MM patients using ICIs either alone or in combination with other therapies has increased, together with the need for reliable biomarkers that can both predict and monitor response to ICIs. In this context, circulating biomarkers, such as DNA, RNA, proteins, and cells, have emerged due to their ability to reflect disease status. Moreover, blood tests are minimally invasive and provide an attractive option to detect biomarkers, avoiding stressful medical procedures. This systematic review aims to evaluate the possibility of a non-invasive biomarker signature that can guide therapeutic decisions. The studies reported here offer valuable insight into how circulating biomarkers can have a role in personalized treatments for melanoma patients receiving ICIs therapy, emphasizing the need for rigorous clinical trials to confirm findings and establish standardized procedures.

Nivolumab + Tacrolimus + Prednisone ± Ipilimumab for Kidney Transplant Recipients With Advanced Cutaneous Cancers

PURPOSE

Cancer-related mortality rates among kidney transplant recipients (KTR) are high, but these patients have largely been excluded from trials of immune checkpoint inhibitors because of immunosuppression and risk of treatment-related allograft loss (TRAL). We conducted a prospective clinical trial testing nivolumab (NIVO) + tacrolimus (TACRO) + prednisone (PRED) ± ipilimumab (IPI) in KTR with advanced cutaneous cancers.

METHODS

Adult KTR with advanced melanoma or basal, cutaneous squamous, or Merkel cell carcinomas were eligible. Immunosuppression was standardized to TACRO (serum trough 2-5 ng/mL) + PRED 5 mg once daily. Patients then received NIVO 480 mg IV once every 4 weeks. The primary composite end point was partial or complete (tumor) response (CR) or stable disease per RECIST v1.1 without allograft loss at 16W. Patients with progressive disease (PD) could receive IPI 1 mg/kg IV + NIVO 3 mg/kg once every 3 weeks × 4 followed by NIVO. Donor-derived cell-free DNA (dd-cfDNA) levels were measured approximately once every 2 weeks as a potential predictor of allograft rejection.

RESULTS

Among eight evaluable patients, none met the trial's primary end point. All eight patients experienced PD on NIVO + TACRO + PRED; TRAL occurred in one patient. Six patients then received IPI + NIVO + TACRO + PRED. Best overall responses: two CR (one with TRAL) and four PD (one with TRAL). In total, 7 of 8 pre-NIVO tumor biopsies contained a paucity of infiltrating immune cells. In total, 2 of 5 on-NIVO biopsies demonstrated moderate immune infiltrates; both patients later experienced a CR to IPI + NIVO. In 2 of 3 patients with TRAL, dd-cfDNA elevations occurred 10 and 15 days before increases in serum creatinine.

CONCLUSION

In most KTR with advanced skin cancer, TACRO + PRED provides insufficient allograft protection and compromises immune-mediated tumor regression after administration of NIVO ± IPI. Elevated dd-cfDNA levels can signal treatment-related allograft rejection earlier than rises in serum creatinine.

Single agent vs combination immunotherapy in advanced melanoma: a review of the evidence

PURPOSE OF REVIEW

The aim of this review is to outline the current landscape of advanced melanoma treatment options, provide insights on selecting combination therapies within different clinical scenarios, capture clinical relevance of anti-programmed cell death protein 1 (PD-1) monotherapy, and explore the unmet needs with immune check-point inhibitors (ICI) in advanced melanoma.

RECENT FINDINGS

ICI based treatment consisted of single agent ICI or dual combination ICI-ICI is the standard of care of front-line treatment of metastatic or unresectable melanoma. PD-1 inhibitors (Pembrolizumab and Nivolumab) improved progression free survival (PFS) and overall survival (OS) compared to chemotherapy and cytotoxic T-lymphocyte associated protein 4 (CTLA-4) inhibitors (Ipilimumab and Tremelimumab). The dual ICI combination (Nivolumab and Ipilimumab) provided profound and durable responses better than monotherapy, and the longest overall survival ever achieved in advanced disease, including in patients with murine sarcoma viral oncogene homolog B (BRAF)-mutated disease, but at the cost of a high risk of severe toxicity. The new dual blockage of LAG-3 and PD-1 (Nivolumab-Relatlimab) emerges as a valid option with promising efficacy outcomes and a favourable toxicity profile. Mature survival data is still needed to capture the real benefit.

SUMMARY

These new plethora of options pose new challenges not only for optimal treatment sequencing strategies but especially for management of adverse effects, endorsing the need to integrate a holistic and personalized approach for patient care.

Prognostic and predictive biomarkers in melanoma

Biomarkers help to inform the clinical management of patients with melanoma. For patients with clinically localised primary melanoma, biomarkers can help to predict post-surgical outcome (including via the use of risk prediction tools), better select patients for sentinel lymph node biopsy, and tailor catch-all follow-up protocols to the individual. Systemic drug treatments, including immune checkpoint inhibitor (ICI) therapies and BRAF-targeted therapies, have radically improved the prognosis of metastatic (stage III and IV) cutaneous melanoma patients, and also shown benefit in the earlier setting of stage IIB/C primary melanoma. Unfortunately, a response is far from guaranteed. Here, we review clinically relevant, established, and emerging, prognostic, and predictive pathological biomarkers that refine clinical decision-making in primary and metastatic melanoma patients. Gene expression profile assays and nomograms are emerging tools for prognostication and sentinel lymph node risk prediction in primary melanoma patients. Biomarkers incorporated into clinical practice guidelines include BRAF V600 mutations for the use of targeted therapies in metastatic cutaneous melanoma, and the HLA-A∗02:01 allele for the use of a bispecific fusion protein in metastatic uveal melanoma. Several predictive biomarkers have been proposed for ICI therapies but have not been incorporated into Australian clinical practice guidelines. Further research, validation, and assessment of clinical utility is required before more prognostic and predictive biomarkers are fluidly integrated into routine care.

Prediction of Effectiveness and Toxicities of Immune Checkpoint Inhibitors Using Real-World Patient Data

PURPOSE

Although immune checkpoint inhibitors (ICIs) have improved outcomes in certain patients with cancer, they can also cause life-threatening immunotoxicities. Predicting immunotoxicity risks alongside response could provide a personalized risk-benefit profile, inform therapeutic decision making, and improve clinical trial cohort selection. We aimed to build a machine learning (ML) framework using routine electronic health record (EHR) data to predict hepatitis, colitis, pneumonitis, and 1-year overall survival.

METHODS

Real-world EHR data of more than 2,200 patients treated with ICI through December 31, 2018, were used to develop predictive models. Using a prediction time point of ICI initiation, a 1-year prediction time window was applied to create binary labels for the four outcomes for each patient. Feature engineering involved aggregating laboratory measurements over appropriate time windows (60-365 days). Patients were randomly partitioned into training (80%) and test (20%) sets. Random forest classifiers were developed using a rigorous model development framework.

RESULTS

The patient cohort had a median age of 63 years and was 61.8% male. Patients predominantly had melanoma (37.8%), lung cancer (27.3%), or genitourinary cancer (16.4%). They were treated with PD-1 (60.4%), PD-L1 (9.0%), and CTLA-4 (19.7%) ICIs. Our models demonstrate reasonably strong performance, with AUCs of 0.739, 0.729, 0.755, and 0.752 for the pneumonitis, hepatitis, colitis, and 1-year overall survival models, respectively. Each model relies on an outcome-specific feature set, though some features are shared among models.

CONCLUSION

To our knowledge, this is the first ML solution that assesses individual ICI risk-benefit profiles based predominantly on routine structured EHR data. As such, use of our ML solution will not require additional data collection or documentation in the clinic.

Predictive Factors in Metastatic Melanoma Treated with Immune Checkpoint Inhibitors: From Clinical Practice to Future Perspective

The introduction of immunotherapy revolutionized the treatment landscape in metastatic melanoma. Despite the impressive results associated with immune checkpoint inhibitors (ICIs), only a portion of patients obtain a response to this treatment. In this scenario, the research of predictive factors is fundamental to identify patients who may have a response and to exclude patients with a low possibility to respond. These factors can be host-associated, immune system activation-related, and tumor-related. Patient-related factors can vary from data obtained by medical history (performance status, age, sex, body mass index, concomitant medications, and comorbidities) to analysis of the gut microbiome from fecal samples. Tumor-related factors can reflect tumor burden (metastatic sites, lactate dehydrogenase, C-reactive protein, and circulating tumor DNA) or can derive from the analysis of tumor samples (driver mutations, tumor-infiltrating lymphocytes, and myeloid cells). Biomarkers evaluating the immune system activation, such as IFN-gamma gene expression profile and analysis of circulating immune cell subsets, have emerged in recent years as significantly correlated with response to ICIs. In this manuscript, we critically reviewed the most updated literature data on the landscape of predictive factors in metastatic melanoma treated with ICIs. We focus on the principal limits and potentiality of different methods, shedding light on the more promising biomarkers.

Sustained improved survival of patients with metastatic melanoma after the introduction of anti-PD-1-based therapies

BACKGROUND

The introduction of modern therapies improved the median survival of patients with metastatic melanoma (MM). Here, we determined the real-world impact of modern treatments on the long-term survival of MM.

METHODS

In a population-based study, we extracted all cases of MM diagnosed in four non-consecutive years marked by major changes in available 1st line treatments (2012, 2014, 2016, and 2018) from the Danish MM Database. Patients were grouped into "trial-like" and "trial-excluded" based on common trial eligibility criteria.

RESULTS

We observed a sustained improved survival of "trial-like" patients diagnosed in 2016 or in 2018, compared to 2012 or 2014, but no major differences in 2018 versus 2016. In contrast, while survival of "trial-excluded" patients in 2016 was better compared to 2014 and 2012, survival in 2018 was improved over all previous years. We then developed a prognostic model based on multivariable stratified Cox regression, to predict the survival of newly diagnosed MM patients. Internal validation showed excellent discrimination and calibration, with a time-area-under-the-curve above 0.79 at multiple time horizons, for up to four years after diagnosis.

CONCLUSIONS

The introduction of modern treatments such as anti-PD-1 has led to a sustained, improved survival of real-world patients with MM, regardless of their eligibility for clinical trials. We provide an updateable prognostic model that can be used to improve patient information. Overall, these data highlight a positive population-based impact of modern treatments and can help health technology assessment agencies worldwide to evaluate the appropriateness of drug pricing based on known cost-benefit data.

Current state and challenges of emerging biomarkers for immunotherapy in hepatocellular carcinoma (Review)

Hepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancer. According to the American Cancer Society, among patients diagnosed with advanced liver cancer, HCC has the sixth-highest incident rate, resulting in a poor prognosis. Surgery, radiofrequency ablation, transcatheter arterial chemoembolization, radiation, chemotherapy, targeted therapy and immunotherapy are the current treatment options available. Immunotherapy, which has emerged as an innovative treatment strategy over the past decade, is serving a vital role in the treatment of advanced liver cancer. Since only a small number of individuals can benefit from immunotherapy, biomarkers are required to help clinicians identify the target populations for this precision medicine. These biomarkers, such as PD-1/PD-L1, tumor mutational burden and circulating tumor DNA, can be used to investigate interactions between immune checkpoint inhibitors and tumors. The present review summarizes information on the currently available biomarkers used for immunotherapy and the challenges that are present.

Real-world outcomes of 18,186 metastatic solid tumor outpatients: Baseline blood cell counts correlate with survival after immune checkpoint inhibitor therapy

BACKGROUND

Patient survival in advanced/metastatic melanoma, non-small cell lung cancer (NSCLC), and renal cell carcinoma (RCC) has improved with immune checkpoint inhibitors (ICI). Biomarkers' role in prognosis and treatment has been limited by conflicting trial results.

METHODS

This retrospective, observational study analyzed baseline demographic, clinical, laboratory, and treatment data versus outcomes of The US Oncology Network adult outpatients. Patients with advanced/metastatic melanoma, NSCLC, or RCC treated between January 1, 2015 and November 30, 2020 were given ICI monotherapy or combination therapy with ipilimumab, pembrolizumab, nivolumab, or atezolizumab. Treatment outcomes (overall survival [OS], time to treatment discontinuation, time to next treatment) were followed longitudinally until May 31, 2021, last patient record, or date of death. Baseline blood cell counts, including absolute monocyte count (AMC), absolute lymphocyte count (ALC), monocyte-to-lymphocyte ratio (MLR), absolute neutrophil count (ANC), and eosinophil count, were subdivided into quintiles for univariate and multivariable Cox regression analyses.

RESULTS

Data from 18,186 patients with advanced/metastatic melanoma (n = 3314), NSCLC (n = 12,416), and RCC (n = 2456) were analyzed. Better OS correlated with increased baseline serum albumin concentration, increased eosinophil and lymphocyte counts, and Western United States physician practice location. Decreased OS correlated with increased AMC, MLR, ANC, age, and worse Eastern Cooperative Oncology Group performance status.

CONCLUSIONS

To our knowledge, this study is the largest to date to associate baseline survival indicators and outcomes in outpatients with advanced/metastatic melanoma, NSCLC, or RCC and receiving ICIs. Results may inform disease-specific prognostic models and help providers identify patients most likely to benefit from ICI therapy.

Dabrafenib plus trametinib versus anti-PD-1 monotherapy as adjuvant therapy in BRAF V600-mutant stage III melanoma after definitive surgery: a multicenter, retrospective cohort study

Background

Both dabrafenib/trametinib (D/T) and anti-PD-1 monotherapy (PD-1) are approved adjuvant therapies for patients with stage III BRAF V600-mutant melanoma. However, there is still a lack of head-to-head comparative data. We aimed to describe efficacy and toxicity outcomes for these two standard therapies across melanoma centers.

Methods

This multicenter, retrospective cohort study was conducted in 15 melanoma centers in Australia, China, Germany, Italy, Japan, UK, and US. We included adult patients with resected stage III BRAF V600-mutant melanoma who received either adjuvant D/T or PD-1 between Jul 2015 and Oct 2022. The primary endpoint was relapse-free survival (RFS). Secondary endpoints included overall survival (OS), recurrence pattern and toxicity.

Findings

We included 598 patients with stage III BRAF V600-mutant melanoma who received either adjuvant D/T (n = 393 [66%]) or PD-1 (n = 205 [34%]) post definitive surgery between Jul 2015 and Oct 2022. At a median follow-up of 33 months (IQR 21-43), the median RFS was 51.0 months (95% CI 41.0-not reached [NR]) in the D/T group, significantly longer than PD-1 (44.8 months [95% CI 28.5-NR]) (univariate: HR 0.66, 95% CI 0.50-0.87, P = 0.003; multivariate: HR 0.58, 95% CI 0.39-0.86, P = 0.007), with comparable OS with PD-1 (multivariate, HR 0.90, 95% CI 0.48-1.70, P = 0.75). Similar findings were observed using a restricted-mean-survival-time model. Among those who experienced recurrence, the proportion of distant metastases was higher in the D/T cohort. D/T had a higher incidence of treatment modification due to adverse events (AEs) than PD-1, but fewer persistent AEs.

Interpretation

In patients with stage III BRAF V600-mutant melanoma post definitive surgery, D/T yielded better RFS than PD-1, with higher transient but lower persistent toxicity, and comparable OS. D/T seems to provide a better outcome compared with PD-1, but a longer follow-up and ideally a large prospective trial are needed.

Funding

Dr. Xue Bai was supported by the Beijing Hospitals Authority Youth Programme (QMS20211101) for her efforts devoted to this study. Dr. Keith T. Flaherty was funded by Adelson Medical Research Foundation for the efforts devoted to this study.

Neutrophil-lymphocyte ratio and platelet-lymphocyte ratio as potential predictive markers of treatment response in cancer patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis

Background

The role of platelet-lymphocyte ratio (PLR) and neutrophil-lymphocyte ratio (NLR) as independent prognostic markers in different tumors is well established. However, there is a limited review of the potential of NLR and PLR as predictors of treatment outcomes from immune checkpoint inhibitors (ICIs).

Objective

To establish a correlation between NLR and PLR and the potential of clinical benefit from ICIs.

Methods

The literature search was performed for studies that reported the association between NLR, PLR, and treatment outcomes among cancer patients treated with ICIs. The outcomes of interest were objective response rate (ORR), disease control rate (DCR), and progressive disease (PD). ORR was the summation of patients who achieved complete response and partial response. DCR included patients who achieved stable disease. PD was the proportion of patients who progressed, relapsed, or discontinued the treatment. Statistical analysis was performed using the STATA 12.0 package. Heterogeneity was determined by the I2 value. Quality assessment was performed using the Newcastle-Ottawa Scale. Egger's test was used to establish publication bias and sensitivity analysis.

Results

A total of 40 papers that met the inclusion criteria were included in the systematic review. However, only 17 studies were used in the meta-analysis to determine the correlation between NLR, PLR, and treatment response. We found that treatment with ICIs and monitoring of outcomes and adverse events using PLR and NLR parameters have been studied in different tumors. Our analysis showed that low NLR correlated with higher ORR (OR = 0.62 (95% CI 0.47-0.81, p = 0.001) and higher DCR (OR = 0.23, 95% CI 0.14-0.36, p < 0.001). Higher NLR predicted a higher probability of PD (OR = 3.12, 95% CI 1.44, 6.77, p = 0.004). Similarly, low PLR correlated with higher ORR (OR = 0.69, 95% CI 0.5, 0.95, p = 0.025). Generally, patients with low NLR and PLR were more likely to achieve clinical benefit and better response (p-value < 0.001). Meanwhile, patients with high ratios were more likely to progress (p-value < 0.005), although there was significant heterogeneity among studies. There was no significant publication bias observed.

Conclusion

The study showed that high NLR and PLR either at baseline or during treatment is associated with poorer treatment outcome. Therefore, these ratios can be utilized in clinical practice with other markers to determine treatment efficacy from immunotherapy.

VEGF Inhibitors Improve Survival Outcomes in Patients with Liver Metastases across Cancer Types-A Meta-Analysis

BACKGROUND

Liver metastases are associated with poor prognosis across cancers. Novel treatment strategies to treat patients with liver metastases are needed. This meta-analysis aimed to assess the efficacy of vascular endothelial growth factor inhibitors in patients with liver metastases across cancers.

METHODS

A systematic search of PubMed, Cochrane CENTRAL, and Embase was performed between January 2000 and April 2023. Randomized controlled trials of patients with liver metastases comparing standard of care (systemic therapy or best supportive care) with or without vascular endothelial growth factor inhibitors were included in the study. Outcomes reported included progression-free survival and overall survival.

RESULTS

A total of 4445 patients with liver metastases from 25 randomized controlled trials were included in this analysis. The addition of vascular endothelial growth factor inhibitors to standard systemic therapy or best supportive care was associated with superior progression-free survival (HR = 0.49; 95% CI, 0.40-0.61) and overall survival (HR = 0.83; 95% CI, 0.74-0.93) in patients with liver metastases. In a subgroup analysis of patients with versus patients without liver metastases, the benefit with vascular endothelial growth factor inhibitors was more pronounced in the group with liver metastases (HR = 0.44) versus without (HR = 0.57) for progression-free survival, but not for overall survival.

CONCLUSION

The addition of vascular endothelial growth factor inhibitors to standard management improved survival outcomes in patients with liver metastasis across cancers.

Correlation of tumor PD-L1 expression in different tissue types and outcome of PD-1-based immunotherapy in metastatic melanoma - analysis of the DeCOG prospective multicenter cohort study ADOREG/TRIM

BACKGROUND

PD-1-based immune checkpoint inhibition (ICI) is the major backbone of current melanoma therapy. Tumor PD-L1 expression represents one of few biomarkers predicting ICI therapy outcome. The objective of the present study was to systematically investigate whether the type of tumor tissue examined for PD-L1 expression has an impact on the correlation with ICI therapy outcome.

METHODS

Pre-treatment tumor tissue was collected within the prospective DeCOG cohort study ADOREG/TRIM (CA209-578; NCT05750511) between February 2014 and May 2020 from 448 consecutive patients who received PD-1-based ICI for non-resectable metastatic melanoma. The primary study endpoint was best overall response (BOR), secondary endpoints were progression-free (PFS) and overall survival (OS). All endpoints were correlated with tumor PD-L1 expression (quantified with clone 28-8; cutoff ≥5%) and stratified by tissue type.

FINDINGS

Tumor PD-L1 was determined in 95 primary tumors (PT; 36.8% positivity), 153 skin/subcutaneous (34.0% positivity), 115 lymph node (LN; 50.4% positivity), and 85 organ (40.8% positivity) metastases. Tumor PD-L1 correlated with BOR if determined in LN (OR = 0.319; 95% CI = 0.138-0.762; P = 0.010), but not in skin/subcutaneous metastases (OR = 0.656; 95% CI = 0.311-1.341; P = 0.26). PD-L1 positivity determined on LN metastases was associated with favorable survival (PFS, HR = 0.490; 95% CI = 0.310-0.775; P = 0.002; OS, HR = 0.519; 95% CI = 0.307-0.880; P = 0.014). PD-L1 positivity determined in PT (PFS, HR = 0.757; 95% CI = 0.467-1.226; P = 0.27; OS; HR = 0.528; 95% CI = 0.305-0.913; P = 0.032) was correlated with survival to a lesser extent. No relevant survival differences were detected by PD-L1 determined in skin/subcutaneous metastases (PFS, HR = 0.825; 95% CI = 0.555-1.226; P = 0.35; OS, HR = 1.083; 95% CI = 0.698-1.681; P = 0.72).

INTERPRETATION

For PD-1-based immunotherapy in melanoma, tumor PD-L1 determined in LN metastases was stronger correlated with therapy outcome than that assessed in PT or organ metastases. PD-L1 determined in skin/subcutaneous metastases showed no outcome correlation and therefore should be used with caution for clinical decision making.

FUNDING

Bristol-Myers Squibb (ADOREG/TRIM, NCT05750511); German Research Foundation (DFG; Clinician Scientist Program UMEA); Else Kröner-Fresenius-Stiftung (EKFS; Medical Scientist Academy UMESciA).

Classification of the tumor immune microenvironment and associations with outcomes in patients with metastatic melanoma treated with immunotherapies

BACKGROUND

Tumor microenvironment (TME) characteristics are potential biomarkers of response to immune checkpoint inhibitors in metastatic melanoma. This study developed a method to perform unsupervised classification of TME of metastatic melanoma.

METHODS

We used multiplex immunohistochemical and quantitative pathology-derived assessment of immune cell compositions of intratumoral and peritumoral regions of metastatic melanoma baseline biopsies to classify TME in relation to response to anti-programmed cell death protein 1 (PD-1) monotherapy or in combination with anti-cytotoxic T-cell lymphocyte-4 (ipilimumab (IPI)+PD-1).

RESULTS

Spatial profiling of CD8+T cells, macrophages, and melanoma cells, as well as phenotypic PD-1 receptor ligand (PD-L1) and CD16 proportions, were used to identify and classify patients into one of three mutually exclusive TME classes: immune-scarce, immune-intermediate, and immune-rich tumors. Patients with immune-rich tumors were characterized by a lower proportion of melanoma cells and higher proportions of immune cells, including higher PD-L1 expression. These patients had higher response rates and longer progression-free survival (PFS) than those with immune-intermediate and immune-scarce tumors. At a median follow-up of 18 months (95% CI: 6.7 to 49 months), the 1-year PFS was 76% (95% CI: 64% to 90%) for patients with an immune-rich tumor, 56% (95% CI: 44% to 72%) for those with an immune-intermediate tumor, and 33% (95% CI: 23% to 47%) for patients with an immune-scarce tumor. A higher response rate was observed in patients with an immune-scarce or immune-intermediate tumor when treated with IPI+PD-1 compared with those treated with PD-1 alone.

CONCLUSIONS

Our study provides an automatic TME classification method that may predict the clinical efficacy of immunotherapy for patients with metastatic melanoma.

Development and Validation of a Prognostic Risk Model for Patients with Advanced Melanoma Treated with Immune Checkpoint Inhibitors

BACKGROUND

Risk stratification tools for patients with advanced melanoma (AM) treated with immune checkpoint inhibitors (ICI) are lacking. We identified a new prognostic model associated with overall survival (OS).

PATIENTS AND METHODS

A total of 318 treatment naïve patients with AM receiving ICI were collected from a multi-centre retrospective cohort study. LASSO Cox regression identified independent prognostic factors associated with OS. Model validation was carried out on 500 iterations of bootstrapped samples. Harrel's C-index was calculated and internally validated to outline the model's discriminatory performance. External validation was carried out in 142 advanced melanoma patients receiving ICI in later lines.

RESULTS

High white blood cell count (WBC), high lactate dehydrogenase (LDH), low albumin, Eastern Cooperative Oncology Group (ECOG) performance status ≥1, and the presence of liver metastases were included in the model. Patients were parsed into 3 risk groups: favorable (0-1 factors) OS of 52.9 months, intermediate (2-3 factors) OS 13.0 months, and poor (≥4 factors) OS 2.7 months. The C-index of the model from the discovery cohort was 0.69. External validation in later-lines (N = 142) of therapy demonstrated a c-index of 0.65.

CONCLUSIONS

Liver metastases, low albumin, high LDH, high WBC, and ECOG≥1 can be combined into a prognostic model for AM patients treated with ICI.

Biomarkers of immune checkpoint inhibitor response and toxicity: Challenges and opportunities

Immune checkpoint inhibitors have transformed cancer therapy, but their optimal use is still constrained by lack of response and toxicity. Biomarkers of response may facilitate drug development by allowing appropriate therapy selection and focusing clinical trial enrollment. However, aside from PD-L1 staining in a subset of tumors and rarely mismatch repair deficiency, no biomarkers are routinely used in the clinic. In addition, severe toxicities may cause severe morbidity, therapy discontinuation, and even death. Here, we review the state of the field with a focus on our research in therapeutic biomarkers and toxicities from immune checkpoint inhibitors.

Cutaneous melanoma

Cutaneous melanoma is a malignancy arising from melanocytes of the skin. Incidence rates are rising, particularly in White populations. Cutaneous melanoma is typically driven by exposure to ultraviolet radiation from natural sunlight and indoor tanning, although there are several subtypes that are not related to ultraviolet radiation exposure. Primary melanomas are often darkly pigmented, but can be amelanotic, with diagnosis based on a combination of clinical and histopathological findings. Primary melanoma is treated with wide excision, with margins determined by tumour thickness. Further treatment depends on the disease stage (following histopathological examination and, where appropriate, sentinel lymph node biopsy) and can include surgery, checkpoint immunotherapy, targeted therapy, or radiotherapy. Systemic drug therapies are recommended as an adjunct to surgery in patients with resectable locoregional metastases and are the mainstay of treatment in advanced melanoma. Management of advanced melanoma is complex, particularly in those with cerebral metastasis. Multidisciplinary care is essential. Systemic drug therapies, particularly immune checkpoint inhibitors, have substantially increased melanoma survival following a series of landmark approvals from 2011 onward.

Immunotherapy: an emerging modality to checkmate brain metastasis

The diagnosis of brain metastasis (BrM) has historically been a dooming diagnosis that is nothing less than a death sentence, with few treatment options for palliation or prolonging life. Among the few treatment options available, brain radiotherapy (RT) and surgical resection have been the backbone of therapy. Within the past couple of years, immunotherapy (IT), alone and in combination with traditional treatments, has emerged as a reckoning force to combat the spread of BrM and shrink tumor burden. This review compiles recent reports describing the potential role of IT in the treatment of BrM in various cancers. It also examines the impact of the tumor microenvironment of BrM on regulating the spread of cancer and the role IT can play in mitigating that spread. Lastly, this review also focuses on the future of IT and new clinical trials pushing the boundaries of IT in BrM.

IMPemBra: a phase 2 study comparing pembrolizumab with intermittent/short-term dual MAPK pathway inhibition plus pembrolizumab in patients with melanoma harboring the BRAFV600 mutation

BACKGROUND

Continuous combination of MAPK pathway inhibition (MAPKi) and anti-programmed death-(ligand) 1 (PD-(L)1) showed high response rates, but only limited improvement in progression-free survival (PFS) at the cost of a high frequency of treatment-related adverse events (TRAE) in patients with BRAF^V600-mutated melanoma. Short-term MAPKi induces T-cell infiltration in patients and is synergistic with anti-programmed death-1 (PD-1) in a preclinical melanoma mouse model. The aim of this phase 2b trial was to identify an optimal regimen of short-term MAPKi with dabrafenib plus trametinib in combination with pembrolizumab.

METHODS

Patients with treatment-naïve BRAF^V600E/K-mutant advanced melanoma started pembrolizumab 200 mg every 3 weeks. In week 6, patients were randomized to continue pembrolizumab only (cohort 1), or to receive, in addition, intermittent dabrafenib 150 mg two times per day plus trametinib 2 mg one time per day for two cycles of 1 week (cohort 2), two cycles of 2 weeks (cohort 3), or continuously for 6 weeks (cohort 4). All cohorts continued pembrolizumab for up to 2 years. Primary endpoints were safety and treatment-adherence. Secondary endpoints were objective response rate (ORR) at week 6, 12, 18 and PFS.

RESULTS

Between June 2016 and August 2018, 33 patients with advanced melanoma have been included and 32 were randomized. Grade 3-4 TRAE were observed in 12%, 12%, 50%, and 63% of patients in cohort 1, 2, 3, and 4, respectively. All planned targeted therapy was given in 88%, 63%, and 38% of patients in cohort 2, 3, and 4. ORR at week 6, 12, and 18 were 38%, 63%, and 63% in cohort 1; 25%, 63%, and 75% in cohort 2; 25%, 50%, and 75% in cohort 3; and 0%, 63%, and 50% in cohort 4. After a median follow-up of 43.5 months, median PFS was 10.6 months for pembrolizumab monotherapy and not reached for patients treated with pembrolizumab and intermittent dabrafenib and trametinib (p=0.17). The 2-year and 3-year landmark PFS were both 25% for cohort 1, both 63% for cohort 2, 50% and 38% for cohort 3 and 75% and 60% for cohort 4.

CONCLUSIONS

The combination of pembrolizumab plus intermittent dabrafenib and trametinib seems more feasible and tolerable than continuous triple therapy. The efficacy is promising and appears to be favorable over pembrolizumab monotherapy.

TRIAL REGISTRATION NUMBER

NCT02625337.

Addressing resistance to PD-1/PD-(L)1 pathway inhibition: considerations for combinatorial clinical trial designs

With multiple PD-(L)1 inhibitors approved across dozens of indications by the US Food and Drug Administration, the number of patients exposed to these agents in adjuvant, first-line metastatic, second-line metastatic, and refractory treatment settings is increasing rapidly. Although some patients will experience durable benefit, many have either no clinical response or see their disease progress following an initial response to therapy. There is a significant need to identify therapeutic approaches to overcome resistance and confer clinical benefits for these patients. PD-1 pathway blockade has the longest history of use in melanoma, non-small cell lung cancer (NSCLC), and renal cell carcinoma (RCC). Therefore, these settings also have the most extensive clinical experience with resistance. In 2021, six non-profit organizations representing patients with these diseases undertook a year-long effort, culminating in a 2-day workshop (including academic, industry, and regulatory participants) to understand the challenges associated with developing effective therapies for patients previously exposed to anti-PD-(L)1 agents and outline recommendations for designing clinical trials in this setting. This manuscript presents key discussion themes and positions reached through this effort, with a specific focus on the topics of eligibility criteria, comparators, and endpoints, as well as tumor-specific trial design options for combination therapies designed to treat patients with melanoma, NSCLC, or RCC after prior PD-(L)1 pathway blockade.

Neoadjuvant Checkpoint Immunotherapy and Melanoma: The Time Is Now

The role of neoadjuvant therapy is undergoing an historic shift in oncology. The emergence of potent immunostimulatory anticancer agents has transformed neoadjuvant therapy from a useful tool in minimizing surgical morbidity to a life-saving treatment with curative promise, led by research in the field of melanoma. Health practitioners have witnessed remarkable improvements in melanoma survival outcomes over the past decade, beginning with checkpoint immunotherapies and BRAF-targeted therapies in the advanced setting that were successfully adopted into the postsurgical adjuvant setting for high-risk resectable disease. Despite substantial reductions in postsurgical recurrence, high-risk resectable melanoma has remained a life-altering and potentially fatal disease. In recent years, data from preclinical models and early-phase clinical trials have pointed to the potential for greater clinical efficacy when checkpoint inhibitors are administered in the neoadjuvant rather than adjuvant setting. Early feasibility studies showed impressive pathologic response rates to neoadjuvant immunotherapy, which were associated with recurrence-free survival rates of over 90%. Recently, the randomized phase II SWOG S1801 trial (ClinicalTrials.gov identifier: NCT03698019) reported a 42% reduction in 2-year event-free survival risk with neoadjuvant versus adjuvant pembrolizumab in resectable stage IIIB-D/IV melanoma (72% v 49%; hazard ratio, 0.58; P = .004), establishing neoadjuvant single-agent immunotherapy as a new standard of care. A randomized phase III trial of neoadjuvant immunotherapy in resectable stage IIIB-D melanoma, NADINA (ClinicalTrials.gov identifier: NCT04949113), is ongoing, as are feasibility studies in high-risk stage II disease. With a swathe of clinical, quality-of-life, and economic benefits, neoadjuvant immunotherapy has the potential to redefine the contemporary management of resectable tumors.

Cross-platform comparison of immune signatures in immunotherapy-treated patients with advanced melanoma using a rank-based scoring approach

BACKGROUND

Gene expression profiling is increasingly being utilised as a diagnostic, prognostic and predictive tool for managing cancer patients. Single-sample scoring approach has been developed to alleviate instability of signature scores due to variations from sample composition. However, it is a challenge to achieve comparable signature scores across different expressional platforms.

METHODS

The pre-treatment biopsies from a total of 158 patients, who have received single-agent anti-PD-1 (n = 84) or anti-PD-1 + anti-CTLA-4 therapy (n = 74), were performed using NanoString PanCancer IO360 Panel. Multiple immune-related signature scores were measured from a single-sample rank-based scoring approach, singscore. We assessed the reproducibility and the performance in reporting immune profile of singscore based on NanoString assay in advance melanoma. To conduct cross-platform analyses, singscores between the immune profiles of NanoString assay and the previous orthogonal whole transcriptome sequencing (WTS) data were compared through linear regression and cross-platform prediction.

RESULTS

singscore-derived signature scores reported significantly high scores in responders in multiple PD-1, MHC-1-, CD8 T-cell-, antigen presentation-, cytokine- and chemokine-related signatures. We found that singscore provided stable and reproducible signature scores among the repeats in different batches and cross-sample normalisations. The cross-platform comparisons confirmed that singscores derived via NanoString and WTS were comparable. When singscore of WTS generated by the overlapping genes to the NanoString gene set, the signatures generated highly correlated cross-platform scores (Spearman correlation interquartile range (IQR) [0.88, 0.92] and r² IQR [0.77, 0.81]) and better prediction on cross-platform response (AUC = 86.3%). The model suggested that Tumour Inflammation Signature (TIS) and Personalised Immunotherapy Platform (PIP) PD-1 are informative signatures for predicting immunotherapy-response outcomes in advanced melanoma patients treated with anti-PD-1-based therapies.

CONCLUSIONS

Overall, the outcome of this study confirms that singscore based on NanoString data is a feasible approach to produce reliable signature scores for determining patients' immune profiles and the potential clinical utility in biomarker implementation, as well as to conduct cross-platform comparisons, such as WTS.

Development and validation of a clinical risk score to predict the occurrence of critical illness in hospitalized patients with SFTS

BACKGROUND

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with high mortality. Early identification of patients who may advance to critical stages is crucial. This investigation aimed to establish models to predict SFTS before it reaches the critical illness stage.

METHODS

Between January 2016 and September 2022, 278 cases have been included in this study. There were 87 demographic and systemic chosen variables. For selecting the predictive variables from the cohort, the LASSO was utilized, and for identifying independent predictors, multivariate logistic regression was performed. Based on these factors, a nomogram was established for critical illness. Concordance index values, decision curve analysis and the area under the curve (AUC) were also examined.

RESULTS

Multivariate logistic regression demonstrated the most important differentiating factors as;> 65 years old (P < 0.001, OR 3.388, 95 % CI 1.767-6.696), elevated serum PT (P = 0.011, OR 6.641, 95 % CI 1.584-31.934), elevated serum TT (P = 0.005, OR 3.384, 95 % CI 1.503-8.491), and elevated serum bicarbonate (P = 0.014, OR 0.242, 95 % CI 0.070-0.707). The C-index of the nomogram was 0.812 (95 % CI: 0.754-0.869), representing good discrimination. The model also showed excellent calibration. The AUC of the nomogram established based on four factors, as mentioned earlier, was 0.806. Furthermore, the model had the excellent net benefit, as revealed by the decision curve analysis.

CONCLUSION

An accurate risk score system built on manifestations noted in patients with SFTS upon admission to hospital, might be advantageous in managing SFTS.

Efficacy and safety of immune checkpoint inhibitors in young adults with metastatic melanoma

BACKGROUND

The integration of immune checkpoint inhibitors (ICI) for the treatment of melanoma has resulted in remarkable and durable responses. Given the potential role of immunosenescence, age may contribute to differential ICI efficacy and toxicity. While older patients have been studied in detail, outcomes from ICI in young patients (≤40 years) are not well characterised.

METHODS

We performed a multi-institutional, retrospective study of patients with advanced melanoma treated with anti-PD-1 monotherapy or ICI combination (ipilimumab and anti-PD-1). Response rates, survival, and toxicities were examined based on age comparing those under 40 years of age with older patients (age 41-70 and ≥ 71 years).

RESULTS

A total of 676 patients were included: 190 patients (28%) aged ≤40 years, 313 (46%) between ages 41-70, and 173 patients (26%) aged ≥71. Patients ≤40 years had higher response rates (53% vs 38%, p = 0.035) and improved progression-free survival (median 13.7 vs 4.0 months, p = 0.032) with combination ICI compared to monotherapy. Progression-free survival was similar among groups while overall survival was inferior in patients >70 years, who had low response rates to combination therapy (28%). ICIs had a similar incidence of severe toxicities, though hepatotoxicity was particularly common in younger patients vs. patients >40 with monotherapy (9% vs. 2%, p = 0.007) or combination ICI (37% vs. 10%, p < 0.001).

CONCLUSIONS

ICIs had comparable efficacy between younger and older patients, although outcomes were superior with combination ICI compared to monotherapy in patients aged ≤40 years. Toxicity incidence was similar across age groups, though organs affected were substantially different.

CT radiomics compared to a clinical model for predicting checkpoint inhibitor treatment outcomes in patients with advanced melanoma

INTRODUCTION

Predicting checkpoint inhibitors treatment outcomes in melanoma is a relevant task, due to the unpredictable and potentially fatal toxicity and high costs for society. However, accurate biomarkers for treatment outcomes are lacking. Radiomics are a technique to quantitatively capture tumour characteristics on readily available computed tomography (CT) imaging. The purpose of this study was to investigate the added value of radiomics for predicting clinical benefit from checkpoint inhibitors in melanoma in a large, multicenter cohort.

METHODS

Patients who received first-line anti-PD1±anti-CTLA4 treatment for advanced cutaneous melanoma were retrospectively identified from nine participating hospitals. For every patient, up to five representative lesions were segmented on baseline CT, and radiomics features were extracted. A machine learning pipeline was trained on the radiomics features to predict clinical benefit, defined as stable disease for more than 6 months or response per RECIST 1.1 criteria. This approach was evaluated using a leave-one-centre-out cross validation and compared to a model based on previously discovered clinical predictors. Lastly, a combination model was built on the radiomics and clinical model.

RESULTS

A total of 620 patients were included, of which 59.2% experienced clinical benefit. The radiomics model achieved an area under the receiver operator characteristic curve (AUROC) of 0.607 [95% CI, 0.562-0.652], lower than that of the clinical model (AUROC=0.646 [95% CI, 0.600-0.692]). The combination model yielded no improvement over the clinical model in terms of discrimination (AUROC=0.636 [95% CI, 0.592-0.680]) or calibration. The output of the radiomics model was significantly correlated with three out of five input variables of the clinical model (p < 0.001).

DISCUSSION

The radiomics model achieved a moderate predictive value of clinical benefit, which was statistically significant. However, a radiomics approach was unable to add value to a simpler clinical model, most likely due to the overlap in predictive information learned by both models. Future research should focus on the application of deep learning, spectral CT-derived radiomics, and a multimodal approach for accurately predicting benefit to checkpoint inhibitor treatment in advanced melanoma.

Lung Immune Therapy Evaluation (LITE) Risk, a Novel Prognostic Model for Patients With Advanced Non-Small Cell Lung Cancer Treated With Immune Checkpoint Blockade

INTRODUCTION/BACKGROUND

Immune checkpoint inhibitors (ICI) have revolutionized non-small cell lung cancer (NSCLC). We aimed to identify baseline characteristics, that are prognostic factors for overall survival (OS) in patients with NSCLC treated with ICI monotherapy, in order to derive the Lung Immune Therapy Evaluation (LITE) risk, a prognostic model.

MATERIALS AND METHODS

Multi-center observational cohort study of patients with advanced NSCLC that received ≥1 dose of ICI monotherapy. The training set (n=342) consisted of patients with NSCLC who received first line ICI. The test set (n=153) used for external validation was a discrete cohort of patients who received second line ICI. 20 candidate prognostic factors were examined. Penalized Cox regression was used for variable selection. Multiple imputation was used to address missingness.

RESULTS

Three baseline characteristics populated the final model: ECOG (0, 1 or ≥2), lactate dehydrogenase>upper limit of normal, and derived neutrophil to lymphocyte ratio ≥3. Patients were parsed into 3 risk groups; favorable (n=146, risk score 0-1), intermediate (n=101, risk score 2) and poor (n=95, risk score ≥3). The c-statistic of the training cohort was 0.702 and 0.694 after bootstrapping. The test cohort c-statistic was 0.664. The median OS for favorable, intermediate and poor LITE risk were; 28.3 months, 9.1 months and 2.1 months respectively. Improving LITE risk group was associated with improved OS, intermediate vs favorable HR 2.08 (95%CI 1.46-2.97, P < .001); poor vs favorable HR 5.21 (95%CI 3.69-7.34, P < .001).

CONCLUSION

A simple prognostic model, utilizing accessible clinical data, can discriminate survival outcomes in patients with advanced NSCLC.

RNF31 represses cell progression and immune evasion via YAP/PD-L1 suppression in triple negative breast Cancer

BACKGROUND

Recently genome-based studies revealed that the abnormality of Hippo signaling is pervasive in TNBC and played important role in cancer progression. RING finger protein 31 (RNF31) comes to RING family E3 ubiquitin ligase. Our previously published studies have revealed RNF31 is elevated in ER positive breast cancer via activating estrogen signaling and suppressing P53 pathway.

METHODS

We used several TNBC cell lines and xenograft models and performed immuno-blots, QPCR, in vivo studies to investigate the function of RNF31 in TNBC progression.

RESULT

Here, we demonstrate that RNF31 plays tumor suppressive function in triple negative breast cancer (TNBC). RNF31 depletion increased TNBC cell proliferation and migration in vitro and in vitro. RNF31 depletion in TNBC coupled with global genomic expression profiling indicated Hippo signaling could be the potential target for RNF31 to exert its function. Further data showed that RNF31 depletion could increase the level of YAP protein, and Hippo signaling target genes expression in several TNBC cell lines, while clinical data illustrated that RNF31 expression correlated with longer relapse-free survival in TNBC patients and reversely correlated with YAP protein level. The molecular biology assays implicated that RNF31 could associate with YAP protein, facilitate YAP poly-ubiquitination and degradation at YAP K76 sites. Interestingly, RNF31 could also repress PDL1 expression and sensitive TNBC immunotherapy via inhibiting Hippo/YAP/PDL1 axis.

CONCLUSIONS

Our study revealed the multi-faced function of RNF31 in different subtypes of breast malignancies, while activation RNF31 could be a plausible strategy for TNBC therapeutics.

Nomogram for predicting prognosis of patients with metastatic melanoma after immunotherapy: A Chinese population-based analysis

Background

Previous studies indicated the evidence that baseline levels of thyroid antibodies, thyroid status, and serum lactate dehydrogenase (LDH) and M stage may influence the prognosis of patients with advanced or metastatic melanoma treated with immune checkpoint inhibitors that targets programmed cell death-1 (PD-1) or programmed death ligand 1, which reported that dramatic improvements in survival rates were observed; however, the presence of controversy has prevented consensus from being reached. Study objectives were to develop a nomogram to identify several prognostic factors in Chinese patients with metastatic melanoma receiving immunotherapy.

Methods

This retrospective study included 231 patients from Sun Yat-sen University Cancer Center, and patients were split into internal cohort (n = 165) and external validation cohort (n = 66). We developed a nomogram for the prediction of response and prognosis on the basis of the levels of serum thyroid peroxidase antibody (A-TPO), free T3 (FT3), and LDH and M stage that were measured at the baseline of anti-PD-1 infusion. In addition, the follow-up lasted at least until 5 years after the treatment or mortality. RECIST v1.1 was used to classify treatment responses.

Results

Chi-square test showed that PD-1 antibody was more effective in patients with melanoma with high level baseline FT4 or earlier M stage. A multivariate Cox analysis showed that baseline FT3 (P = 0.009), baseline A-TPO (P = 0.016), and LDH (P = 0.013) levels and M stage (P < 0.001) independently predicted overall survival (OS) in patients with melanoma. The above factors are integrated, and a prediction model is established, i.e., nomogram. Survival probability area-under-the-curve values of 1, 2, and 3 years in the training, internal validation, and external validation cohorts showed the prognostic accuracy and clinical applicability of nomogram (training: 0.714, 0.757, and 0.764; internal validation: 0.7171963, 0.756549, and 0.7651486; external validation: 0.748, 0.710, and 0.856). In addition, the OS of low-risk (total score ≤ 142.65) versus high-risk (total score > 142.65) patients varied significantly in both training group (P < 0.0001) and external validation cohort (P = 0.0012).

Conclusions

According to this study, baseline biomarkers are associated with response to immunotherapy and prognosis among patients with metastatic melanoma. Treatment regimens can be tailor-made on the basis of these biomarkers.

The effect of organ-specific tumor microenvironments on response patterns to immunotherapy

Immunotherapy, particularly immune checkpoint inhibitors, have become widely used in various settings across many different cancer types in recent years. Whilst patients are often treated on the basis of the primary cancer type and clinical stage, recent studies have highlighted disparity in response to immune checkpoint inhibitors at different sites of metastasis, and their impact on overall response and survival. Studies exploring the tumor immune microenvironment at different organ sites have provided insights into the immune-related mechanisms behind organ-specific patterns of response to immunotherapy. In this review, we aimed to highlight the key learnings from clinical studies across various cancers including melanoma, lung cancer, renal cell carcinoma, colorectal cancer, breast cancer and others, assessing the association of site of metastasis and response to immune checkpoint inhibitors. We also summarize the key clinical and pre-clinical findings from studies exploring the immune microenvironment of specific sites of metastasis. Ultimately, further characterization of the tumor immune microenvironment at different metastatic sites, and understanding the biological drivers of these differences, may identify organ-specific mechanisms of resistance, which will lead to more personalized treatment approaches for patients with innate or acquired resistance to immunotherapy.

Circulating cell-free messenger RNA enables non-invasive pan-tumour monitoring of melanoma therapy independent of the mutational genotype

BACKGROUND

Plasma-derived tumour-specific cell-free nucleic acids are increasingly utilized as a minimally invasive, real-time biomarker approach in many solid tumours. Circulating tumour DNA of melanoma-specific mutations is currently the best studied liquid biopsy biomarker for melanoma. However, the combination of hotspot genetic alterations covers only around 80% of all melanoma patients. Therefore, alternative approaches are needed to enable the follow-up of all genotypes, including wild-type.

METHODS

We identified KPNA2, DTL, BACE2 and DTYMK messenger RNA (mRNA) upregulated in melanoma versus nevi tissues by unsupervised data mining (N = 175 melanoma, N = 20 normal skin, N = 6 benign nevi) and experimentally confirmed differential mRNA expression in vitro (N = 18 melanoma, N = 8 benign nevi). Circulating cell-free RNA (cfRNA) was analysed in 361 plasma samples (collected before and during therapy) from 100 melanoma patients and 18 healthy donors. Absolute cfRNA copies were quantified on droplet digital PCR.

RESULTS

KPNA2, DTL, BACE2 and DTYMK cfRNA demonstrated high diagnostic accuracy between melanoma patients' and healthy donors' plasma (AUC > 86%, p < .0001). cfRNA copies increased proportionally with increasing tumour burden independently of demographic variables and even remained elevated in individuals with radiological absence of disease. Re-analysis of single-cell transcriptomes revealed a pan-tumour origin of cfRNA, including endothelial, cancer-associated fibroblasts, macrophages and B cells beyond melanoma cells as cellular sources. Low baseline cfRNA levels were associated with significantly longer progression-free survival (PFS) (KPNA2 HR = .54, p = .0362; DTL HR = .60, p = .0349) and overall survival (KPNA2 HR = .52, p = .0237; BACE2 HR = .55, p = .0419; DTYMK HR = .43, p = .0393). Lastly, we found that cfRNA copies significantly increased during therapy in non-responders compared to responders regardless of therapy and mutational subtypes and that the increase of KPNA2 (HR = 1.73, p = .0441) and DTYMK (HR = 1.82, p = .018) cfRNA during therapy was predictive of shorter PFS.

CONCLUSIONS

In sum, we identified a new panel of cfRNAs for a pan-tumour liquid biopsy approach and demonstrated its utility as a prognostic, therapy-monitoring tool independent of the melanoma mutational genotype.

Clinical Factors Associated with Long-Term Survival in Metastatic Melanoma Treated with Anti-PD1 Alone or in Combination with Ipilimumab

Immune checkpoint inhibitors (ICIs) for treatment of metastatic melanoma (MM) offer lasting overall survival (OS) benefit in a subset of patients. However, outcomes remain poor for non-responders. Clinical predictors of long-term survival remain elusive. We utilized the Alberta Immunotherapy Database to investigate the association of host and disease characteristics, and treatment factors with overall survival (OS) greater than 3 years. We identified patients treated between August 2013 and May 2020 with single-agent anti-PD1 or combination (anti-PD1 and anti-CTLA4) ICI regimens. A logistic regression model was used to assess for independent association between clinical factors captured and survival greater than 3 years. Statistically significant factors on univariable analysis were assessed using multivariable analysis. In total, 284 of 460 patients were identified to have short-term (<1 year) or long-term (>3 years) survival with 186 surviving <1 year and 98 surviving >3 years. The median age was 64 and 18.4% of patients were ECOG ≥ 2. On logistic regression, Breslow's Depth ≤ 4 mm, normal serum LDH, normal serum albumin and M-stage 1a/b were associated with OS > 3 years on univariable and multivariable analysis. ECOG < 2, dNLR ≤ 3, normal hemoglobin were only associated with survival on the univariable analysis but not in the multivariable analysis. The objective response rate in long-term survivors was 83.7% compared to 7.5% in the short-term survivors. Our study identifies four easily accessible predictors of long-term survival in a large real-world MM cohort treated with ICI.

Causes, consequences and clinical significance of aneuploidy across melanoma subtypes

Aneuploidy, the state of the cell in which the number of whole chromosomes or chromosome arms becomes imbalanced, has been recognized as playing a pivotal role in tumor evolution for over 100 years. In melanoma, the extent of aneuploidy, as well as the chromosomal regions that are affected differ across subtypes, indicative of distinct drivers of disease. Multiple studies have suggested a role for aneuploidy in diagnosis and prognosis of melanomas, as well as in the context of immunotherapy response. A number of key constituents of the cell cycle have been implicated in aneuploidy acquisition in melanoma, including several driver mutations. Here, we review the state of the art on aneuploidy in different melanoma subtypes, discuss the potential drivers, mechanisms underlying aneuploidy acquisition as well as its value in patient diagnosis, prognosis and response to immunotherapy treatment.

Neoadjuvant therapy for melanoma: A critical appraisal

The treatment of advanced melanoma has significantly changed since the development of targeted and immune therapy. To date, these agents have primarily been used in the adjuvant or metastatic setting. Given several theoretical advantages, there is increased interest in the use of these new therapeutics in the neoadjuvant setting. In this review, we detail the potential benefits and pitfalls of neoadjuvant therapy for melanoma, review the currently available data, and describe ongoing neoadjuvant trials.

Modified Radical Mastectomy in De Novo Stage IV Inflammatory Breast Cancer

BACKGROUND

There are few studies on surgical management in patients with de novo metastatic inflammatory breast cancer (IBC). The objective of this study is to examine the association between modified radical mastectomy (MRM) and disease-specific survival (DSS) in patients with de novo stage IV IBC.

PATIENTS AND METHODS

The Surveillance, Epidemiology, and End Result Program was queried for patients ≥18 years old with cT4d/pT4d pathology, histology type 8530 and 8533 with distant disease between 2010 and 2016. The sample was divided into two groups: (1) the MRM group, defined as MRM or mastectomy with at least ten lymph nodes removed, and (2) the no-surgery group. Sociodemographic and clinical variables were compared between the groups on bivariable analysis. After propensity score matching, Kaplan-Meier curves and a Cox proportional-hazards model examined DSS.

RESULTS

1293 patients were included in the study, of whom 240 underwent MRM. A higher percentage in the MRM group had only one metastatic site (69.8% versus 52.2%), received chemotherapy (88.3% versus 66.1%) and radiation (58.8% versus 26.0%) compared with the no-MRM group. MRM was associated with an increase in DSS compared with no MRM [HR 0.63 (95% CI 0.50-0.80), p < 0.001]. Patients with MRM had a 5-year DSS rate of 31.4% compared with 17.7% for patients not undergoing surgery (p = 0.001). Survival time was 38 months (range 27-45 months) for the MRM group versus 27 months (22-29 months) for the no-MRM group.

CONCLUSION

MRM in patients with de novo metastatic IBC may improve DSS in a subset of patients.

Current State of Adjuvant Therapy for Melanoma: Less Is More, or More Is Better?

Advances in melanoma treatments over the past decade have changed the course of survival for patients. Several adjuvant therapies have been approved and are now considered standard of care for high-risk patients. These therapies have shown improvements for recurrence-free survival and distant metastases-free survival, but not overall survival, as the data are maturing. The 5-year recurrence-free survival in the COMBI-AD study, which compared dabrafenib and trametinib with placebo, was 65% and 58%, respectively. In the KEYNOTE-054 study, the recurrence-free survival at 3 years was 63.7% versus 41%. Despite these advances, approximately 50% of patients will succumb to their disease. Adjuvant therapy is considered potentially curative and avoids the morbidity of relapsed disease and the poor outcomes seen in metastatic disease. However, the lack of overall survival benefit in clinical trials of patients with high-risk stage II and stage III disease raises the question of whether it is more efficacious to treat when there is residual microscopic disease, or to wait until the disease recurs to avoid treating those who may have been cured by surgery alone. Immunotherapy also has the potential for substantial toxicity that may be lifelong; hence, discussion of risks and benefits of therapy is warranted because there should be less tolerance for substantial toxicity in the adjuvant setting. Adjuvant trials are needed that will integrate biomarkers to allow for better selection of patients who will truly benefit from adjuvant therapy.