A comprehensive analysis of clinical and polygenic germline influences on somatic mutational burden.

Tumor mutational burden (TMB), the total number of somatic mutations in the tumor, and copy number burden (CNB), the corresponding measure of aneuploidy, are established fundamental somatic features and emerging biomarkers for immunotherapy. However, the genetic and non-genetic influences on TMB/CNB and, critically, the manner by which they influence patient outcomes remain poorly understood. Here, we present a large germline-somatic study of TMB/CNB with >23,000 individuals across 17 cancer types, of which 12,000 also have extensive clinical, treatment, and overall survival (OS) measurements available. We report dozens of clinical associations with TMB/CNB, observing older age and male sex to have a strong effect on TMB and weaker impact on CNB. We additionally identified significant germline influences on TMB/CNB, including fine-scale European ancestry and germline polygenic risk scores (PRSs) for smoking, tanning, white blood cell counts, and educational attainment. We quantify the causal effect of exposures on somatic mutational processes using Mendelian randomization. Many of the identified features associated with TMB/CNB were additionally associated with OS for individuals treated at a single tertiary cancer center. For individuals receiving immunotherapy, we observed a complex relationship between PRSs for educational attainment, self-reported college attainment, TMB, and survival, suggesting that the influence of this biomarker may be substantially modified by socioeconomic status. While the accumulation of somatic alterations is a stochastic process, our work demonstrates that it can be shaped by host characteristics including germline genetics.

A radiomics model to predict γδ T-cell abundance and overall survival in head and neck squamous cell carcinoma.

γδ T cells are becoming increasingly popular because of their attractive potential for antitumor immunotherapy. However, the role and assessment of γδ T cells in head and neck squamous cell carcinoma (HNSCC) are not well understood. We aimed to explore the prognostic value of γδ T cell and predict its abundance using a radiomics model. Computer tomography images with corresponding gene expression data and clinicopathological data were obtained from online databases. After outlining the volumes of interest manually, the radiomic features were screened using maximum melevance minimum redundancy and recursive feature elimination algorithms. A radiomics model was developed to predict γδ T-cell abundance using gradient boosting machine. Kaplan-Meier survival curves and univariate and multivariate Cox regression analyses were used for the survival analysis. In this study, we confirmed that γδ T-cell abundance was an independent predictor of favorable overall survival (OS) in patients with HNSCC. Moreover, a radiomics model was built to predict the γδ T-cell abundance level (the areas under the operating characteristic curves of 0.847 and 0.798 in the training and validation sets, respectively). The calibration and decision curves analysis demonstrated the fitness of the model. The high radiomic score was an independent protective factor for OS. Our results indicated that γδ T-cell abundance was a promising prognostic predictor in HNSCC, and the radiomics model could discriminate its abundance levels and predict OS. The noninvasive radiomics model provided a potentially powerful prediction tool to aid clinical judgment and antitumor immunotherapy.

Proteomic profiling of ovarian clear cell carcinomas identifies prognostic biomarkers for chemotherapy.

Clear cell ovarian carcinoma (CCOC) is a relatively rare subtype of ovarian cancer (OC) with high degree of resistance to standard chemotherapy. Little is known about the underlying molecular mechanisms, and it remains a challenge to predict its prognosis after chemotherapy. Here, we first analyzed the proteome of 35 formalin-fixed paraffin-embedded (FFPE) CCOC tissue specimens from a cohort of 32 patients with CCOC (H1 cohort) and characterized 8697 proteins using data-independent acquisition mass spectrometry (DIA-MS). We then performed proteomic analysis of 28 fresh frozen (FF) CCOC tissue specimens from an independent cohort of 24 patients with CCOC (H2 cohort), leading to the identification of 9409 proteins with DIA-MS. After bioinformatics analysis, we narrowed our focus to 15 proteins significantly correlated with the recurrence free survival (RFS) in both cohorts. These proteins are mainly involved in DNA damage response, extracellular matrix (ECM), and mitochondrial metabolism. Parallel reaction monitoring (PRM)-MS was adopted to validate the prognostic potential of the 15 proteins in the H1 cohort and an independent confirmation cohort (H3 cohort). Interferon-inducible transmembrane protein 1 (IFITM1) was observed as a robust prognostic marker for CCOC in both PRM data and immunohistochemistry (IHC) data. Taken together, this study presents a CCOC proteomic data resource and a single promising protein, IFITM1, which could potentially predict the recurrence and survival of CCOC.

Unravelling tumour cell diversity and prognostic signatures in cutaneous melanoma through machine learning analysis.

Melanoma, a highly malignant tumour, presents significant challenges due to its cellular heterogeneity, yet research on this aspect in cutaneous melanoma remains limited. In this study, we utilized single-cell data from 92,521 cells to explore the tumour cell landscape. Through clustering analysis, we identified six distinct cell clusters and investigated their differentiation and metabolic heterogeneity using multi-omics approaches. Notably, cytotrace analysis and pseudotime trajectories revealed distinct stages of tumour cell differentiation, which have implications for patient survival. By leveraging markers from these clusters, we developed a tumour cell-specific machine learning model (TCM). This model not only predicts patient outcomes and responses to immunotherapy, but also distinguishes between genomically stable and unstable tumours and identifies inflamed ('hot') versus non-inflamed ('cold') tumours. Intriguingly, the TCM score showed a strong association with TOMM40, which we experimentally validated as an oncogene promoting tumour proliferation, invasion and migration. Overall, our findings introduce a novel biomarker score that aids in selecting melanoma patients for improved prognoses and targeted immunotherapy, thereby guiding clinical treatment decisions.

Advancing lung adenocarcinoma prognosis and immunotherapy prediction with a multi-omics consensus machine learning approach.

Lung adenocarcinoma (LUAD) is a tumour characterized by high tumour heterogeneity. Although there are numerous prognostic and immunotherapeutic options available for LUAD, there is a dearth of precise, individualized treatment plans. We integrated mRNA, lncRNA, microRNA, methylation and mutation data from the TCGA database for LUAD. Utilizing ten clustering algorithms, we identified stable multi-omics consensus clusters (MOCs). These data were then amalgamated with ten machine learning approaches to develop a robust model capable of reliably identifying patient prognosis and predicting immunotherapy outcomes. Through ten clustering algorithms, two prognostically relevant MOCs were identified, with MOC2 showing more favourable outcomes. We subsequently constructed a MOCs-associated machine learning model (MOCM) based on eight MOCs-specific hub genes. Patients characterized by a lower MOCM score exhibited better overall survival and responses to immunotherapy. These findings were consistent across multiple datasets, and compared to many previously published LUAD biomarkers, our MOCM score demonstrated superior predictive performance. Notably, the low MOCM group was more inclined towards 'hot' tumours, characterized by higher levels of immune cell infiltration. Intriguingly, a significant positive correlation between GJB3 and the MOCM score (R = 0.77, p < 0.01) was discovered. Further experiments confirmed that GJB3 significantly enhances LUAD proliferation, invasion and migration, indicating its potential as a key target for LUAD treatment. Our developed MOCM score accurately predicts the prognosis of LUAD patients and identifies potential beneficiaries of immunotherapy, offering broad clinical applicability.

KIF2C/MCAK a prognostic biomarker and its oncogenic potential in malignant progression, and prognosis of cancer patients: a systematic review and meta-analysis as biomarker.

KIF2C/MCAK (KIF2C) is the most well-characterized member of the kinesin-13 family, which is critical in the regulation of microtubule (MT) dynamics during mitosis, as well as interphase. This systematic review briefly describes the important structural elements of KIF2C, its regulation by multiple molecular mechanisms, and its broad cellular functions. Furthermore, it systematically summarizes its oncogenic potential in malignant progression and performs a meta-analysis of its prognostic value in cancer patients. KIF2C was shown to be involved in multiple crucial cellular processes including cell migration and invasion, DNA repair, senescence induction and immune modulation, which are all known to be critical during the development of malignant tumors. Indeed, an increasing number of publications indicate that KIF2C is aberrantly expressed in multiple cancer entities. Consequently, we have highlighted its involvement in at least five hallmarks of cancer, namely: genome instability, resisting cell death, activating invasion and metastasis, avoiding immune destruction and cellular senescence. This was followed by a systematic search of KIF2C/MCAK's expression in various malignant tumor entities and its correlation with clinicopathologic features. Available data were pooled into multiple weighted meta-analyses for the correlation between KIF2Chigh protein or gene expression and the overall survival in breast cancer, non-small cell lung cancer and hepatocellular carcinoma patients. Furthermore, high expression of KIF2C was correlated to disease-free survival of hepatocellular carcinoma. All meta-analyses showed poor prognosis for cancer patients with KIF2Chigh expression, associated with a decreased overall survival and reduced disease-free survival, indicating KIF2C's oncogenic potential in malignant progression and as a prognostic marker. This work delineated the promising research perspective of KIF2C with modern in vivo and in vitro technologies to further decipher the function of KIF2C in malignant tumor development and progression. This might help to establish KIF2C as a biomarker for the diagnosis or evaluation of at least three cancer entities.

Increased risk of contralateral breast cancer for BRCA1/2 wild-type, high-risk Korean breast cancer patients: a retrospective cohort study.

BACKGROUND: This study aimed to investigate the contralateral breast cancer (CBC) recurrence rate in Korean breast cancer patients according to their BRCA1/2 germline mutation status, focusing particularly on the CBC recurrence risk in BRCA1/2 negative (BRCAx) patients. METHODS: We conducted a retrospective study on 13,107 primary breast cancer patients. The patients were divided into high-risk and low-risk groups for hereditary breast cancer based on the Korean National Health Insurance Service's eligibility criteria for BRCA1/2 germline mutation testing. The high-risk group was further categorized into the BRCA mutation group, the BRCAx group, and the not tested group. We evaluated the overall survival and cumulative risk of developing CBC in these patients. RESULTS: Among 4494 high-risk patients, 973 (21.7%) underwent genetic testing for BRCA1/2 germline mutation, revealing mutations in 158 patients (16.2%). We observed significant overall survival differences across all four groups, with the high-risk, not-tested group demonstrating notably worse overall survival (p < 0.001). However, when adjusted for other prognostic factors, there was no significant differences in hazard ratio of death between the four groups. The cumulative risk of CBC also varied among the groups. Patients with BRCA1/2 mutations showed a 7.3-fold increased risk of CBC compared to the low-risk group (95% CI 4.11-13.0, p < 0.001). Interestingly, BRCAx patients also demonstrated a significantly higher risk of CBC (HR 2.77, 95% CI 1.76-4.35, p < 0.001). The prognostic importance of the BRCAx for CBC recurrence persisted after adjusting for the age and subtype, but became insignificant when the family history of breast cancer was adjusted. CONCLUSION: Breast cancer patients who are at high risk of hereditary breast cancer but with wild-type BRCA 1/2 genes (BRCAx) have increased risk of developing contralateral breast cancer when compared to the low-risk patients. More careful surveillance and follow-up can be offered to these patients especially when they have family history of breast cancer.

Contemporary survival in metastatic bladder cancer patients: A population-based study.

The overall survival (OS) improvement after the advent of several novel systemic therapies, designed for treatment of metastatic urothelial carcinoma of the urinary bladder (mUCUB), is not conclusively studied in either contemporary UCUB patients and/or non-UCUB patients. Within the Surveillance, Epidemiology, and End Results database, contemporary (2017-2020) and historical (2000-2016) systemic therapy-exposed metastatic UCUB and, subsequently, non-UCUB patients were identified. Separate Kaplan-Meier and multivariable Cox regression (CRM) analyses first addressed OS in mUCUB and, subsequently, in metastatic non-UCUB (mn-UCUB). Of 3443 systemic therapy-exposed patients, 2725 (79%) harbored mUCUB versus 709 (21%) harbored mn-UCUB. Of 2725 mUCUB patients, 582 (21%) were contemporary (2017-2020) versus 2143 (79%) were historical (2000-2016). In mUCUB, median OS was 11 months in contemporary versus 8 months in historical patients (Δ = 3 months; p < .0001). After multivariable CRM, contemporary membership status (2017-2020) independently predicted lower overall mortality (OM; hazard ratio [HR] = 0.68, 95% confidence interval [CI] = 0.60-0.76; p < .001). Of 709 mn-UCUB patients, 167 (24%) were contemporary (2017-2020) and 542 (76%) were historical (2000-2016). In mn-UCUB, median OS was 8 months in contemporary versus 7 months in historical patients (Δ = 1 month; p = .034). After multivariable CRM, contemporary membership status (2017-2020) was associated with HR of 0.81 (95% CI = 0.66-1.01; p = .06). In conclusion, contemporary systemic therapy-exposed metastatic patients exhibited better OS in UCUB. However, the magnitude of survival benefit was threefold higher in mUCUB and approximated the survival benefits recorded in prospective randomized trials of novel systemic therapies.

Combination of high anti-SKI and low anti-TMED5 antibody levels is preferable prognostic factor in esophageal carcinoma.

Given that esophageal cancer is highly malignant, the discovery of novel prognostic markers is eagerly awaited. We performed serological identification of antigens by recombinant cDNA expression cloning (SEREX) and identified SKI proto-oncogene protein and transmembrane p24 trafficking protein 5 (TMED5) as antigens recognized by serum IgG antibodies in patients with esophageal carcinoma. SKI and TMED5 proteins were expressed in Escherichia coli, purified by affinity chromatography, and used as antigens. The serum anti-SKI antibody (s-SKI-Ab) and anti-TMED5 antibody (s-TMED5-Ab) levels were significantly higher in 192 patients with esophageal carcinoma than in 96 healthy donors. The presence of s-SKI-Abs and s-TMED5-Abs in the patients' sera was confirmed by western blotting. Immunohistochemical staining showed that the TMED5 protein was highly expressed in the cytoplasm and nuclear compartments of the esophageal squamous cell carcinoma tissues, whereas the SKI protein was localized predominantly in the nuclei. Regarding the overall survival in 91 patients who underwent radical surgery, the s-SKI-Ab-positive and s-TMED5-Ab-negative statuses were significantly associated with a favorable prognosis. Additionally, the combination of s-SKI-Ab-positive and s-TMED5-Ab-negative cases showed an even clearer difference in overall survival as compared with that of s-SKI-Ab-negative and s-TMED5-Ab-positive cases. The s-SKI-Ab and s-TMED5-Ab biomarkers are useful for diagnosing esophageal carcinoma and distinguishing between favorable and poor prognoses.

Metabolism score and machine learning models for the prediction of esophageal squamous cell carcinoma progression.

The incomplete prediction of prognosis in esophageal squamous cell carcinoma (ESCC) patients is attributed to various therapeutic interventions and complex prognostic factors. Consequently, there is a pressing demand for enhanced predictive biomarkers that can facilitate clinical management and treatment decisions. This study recruited 491 ESCC patients who underwent surgical treatment at Huashan Hospital, Fudan University. We incorporated 14 blood metabolic indicators and identified independent prognostic indicators for overall survival through univariate and multivariate analyses. Subsequently, a metabolism score formula was established based on the biochemical markers. We constructed a nomogram and machine learning models utilizing the metabolism score and clinically significant prognostic features, followed by an evaluation of their predictive accuracy and performance. We identified alkaline phosphatase, free fatty acids, homocysteine, lactate dehydrogenase, and triglycerides as independent prognostic indicators for ESCC. Subsequently, based on these five indicators, we established a metabolism score that serves as an independent prognostic factor in ESCC patients. By utilizing this metabolism score in conjunction with clinical features, a nomogram can precisely predict the prognosis of ESCC patients, achieving an area under the curve (AUC) of 0.89. The random forest (RF) model showed superior predictive ability (AUC = 0.90, accuracy = 86%, Matthews correlation coefficient = 0.55). Finally, we used an RF model with optimal performance to establish an online predictive tool. The metabolism score developed in this study serves as an independent prognostic indicator for ESCC patients.

Survival of patients with lymph node versus bone versus visceral metastases according to CHAARTED/LATITUDE criteria in the era of intensified combination therapies for metastatic hormone-sensitive prostate cancer.

BACKGROUND: The first approvals of novel systemic therapies within recent years for metastatic hormone-sensitive (mHSPC) were mainly based on improved overall survival (OS) and time to castration resistance (ttCRPC) in mHSPC patients stratified according to CHAARTED low (LV) versus high volume (HV) and LATITUDE low (LR) versus high-risk (HR) disease. METHODS: Relying on our institutional tertiary-care database we identified all mHSPC stratified according to CHAARTED LV versus HV, LATITUDE LR versus HR and the location of the metastatic spread (lymph nodes (M1a) versus bone (M1b) versus visceral/others (M1c) metastases. OS and ttCRPC analyses, as well as Cox regression models were performed according to different metastatic categories. RESULTS: Of 451 mHSPC, 14% versus 27% versus 48% versus 12% were classified as M1a LV versus M1b LV versus M1b HV versus M1c HV with significant differences in median OS: 95 versus 64 versus 50 versus 46 months (p < 0.001). In multivariable Cox regression models HV M1b (Hazard Ratio: 2.4, p = 0.03) and HV M1c (Hazard Ratio: 3.3, p < 0.01) harbored significant worse than M1a LV mHSPC. After stratification according to LATITUDE criteria, also significant differences between M1a LR versus M1b LR versus M1b HR versus M1c HR mHSPC patients were observed (p < 0.01) with M1b HR (Hazard Ratio: 2.7, p = 0.03) and M1c HR (Hazard Ratio: 3.5, p < 0.01), as predictor for worse OS. In comparison between HV M1b and HV M1c, as well as HR M1b versus HR M1c no differences in ttCRPC or OS were observed. CONCLUSIONS: Significant differences exist between different metastatic patterns of HV and LV and HR and LR criteria. Best prognosis is observed within M1a LV and LR mHSPC patients.

The changing landscape of small cell lung cancer.

BACKGROUND: Small-cell lung cancer (SCLC) is characterized by rapid proliferation and early dissemination. The objective of this study was to examine the demographic trends and outcomes in SCLC. METHODS: The authors queried the National Cancer Institute's Surveillance, Epidemiology, and End Results database to assess the trends in incidence, demographics, staging, and survival for SCLC from 1975 to 2019. Trends were determined using joinpoint analysis according to the year of diagnosis. RESULTS: Among the 530,198 patients with lung cancer, there were 73,362 (13.8%) with SCLC. The incidence per 100,000 population peaked at 15.3 in 1986 followed by a decline to 6.5 in 2019. The percentage of SCLC among all lung tumors increased from 13.3% in 1975 to a peak of 17.5% in 1986, declining to 11.1% by 2019. There was an increased median age at diagnosis from 63 to 69 years and an increased percentage of women from 31.4% to 51.2%. The percentage of stage IV increased from 58.6% in 1988 to 70.8% in 2010, without further increase. The most common sites of metastasis at diagnosis were mediastinal lymph nodes (75.3%) liver (31.6%), bone (23.7%), and brain (16.4%). The 1-year and 5-year overall survival rate increased from 23% and 3.6%, respectively, in 1975-1979 to 30.8% and 6.8%, respectively, in 2010-2019. CONCLUSIONS: The incidence of SCLC peaked in 1988 followed by a gradual decline. Other notable changes include increased median age at diagnosis, the percentage of women, and the percentage of stage IV at diagnosis. The improvement in 5-year overall survival has been statistically significant but clinically modest.

Effect of body mass index on the prognosis of children and adolescents with high-grade mature B-cell non-Hodgkin lymphoma.

BACKGROUND: Little progress has been made in determining the prognostic factors for children and adolescents with high-grade mature B-cell non-Hodgkin lymphoma (HG B-NHL). Based on the important role of body mass index (BMI) in cancer, this study explored the effect of BMI on the prognosis of patients with HG B-NHL. METHODS: Patients aged <18 years with newly diagnosed HG B-NHL were enrolled. Patients were divided into normal, overweight, obese, and emaciated BMI groups according to the growth criteria for children and adolescents. RESULTS: In total, 435 patients were enrolled in this study. There were 329 (75.6%), 46 (10.6%), 13 (3.0%), and 47 (10.8%) patients stratified into the normal, overweight, obese, and emaciated BMI groups, respectively. The event-free survival and overall survival rates of the entire cohort were 89.3% and 92.4%, respectively. The 5-year event-free survival rate for the patients with obese BMI was worse than those with overweight BMI (76.2% vs. 95.6%, p = .04). The 5-year overall survival rate for the patients with emaciated BMI was worse than those with normal (84.5% vs. 93.1%, p = .04) or overweight BMI (84.5% vs. 97.7%, p = .03). Cox multivariate analysis showed that obese or emaciated BMI at diagnosis was associated with an increased risk of death (p = 0.04; HR, 2.26) and was identified as an independent adverse prognostic factor in pediatric HG B-NHL. CONCLUSION: Obese or emaciated BMI at diagnosis is associated with poor prognosis in pediatric HG B-NHL and can be used for risk stratification.

The systematic identification of survival-related alternative splicing events and splicing factors in glioblastoma.

Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor, making it one of the most life-threatening human cancers. Nevertheless, research on the mechanism of action between alternative splicing (AS) and splicing factor (SF) or biomarkers in GBM is limited. AS is a crucial post-transcriptional regulatory mechanism. More than 95% of human genes undergo AS events. AS can diversify the expression patterns of genes, thereby increasing the diversity of proteins and playing a significant role in the occurrence and development of tumors. In this study, we downloaded 599 clinical data and 169 transcriptome analysis data from The Cancer Genome Atlas (TCGA) database. Besides, we collected AS data about GBM from TCGA-SpliceSeq. The overall survival (OS) related AS events in GBM were determined through least absolute shrinkage and selection operator (Lasso) and Cox analysis. Subsequently, the association of these 1825 OS-related AS events with patient survival was validated using the Kaplan-Meier survival analysis, receiver operating characteristic curve, risk curve analysis, and independent prognostic analysis. Finally, we depicted the AS-SF regulatory network, illustrating the interactions between splicing factors and various AS events in GBM. Additionally, we identified three splicing factors (RNU4-1, SEC31B, and CLK1) associated with patient survival. In conclusion, based on AS occurrences, we developed a predictive risk model and constructed an interaction network between GBM-related AS events and SFs, aiming to shed light on the underlying mechanisms of GBM pathogenesis and progression.

Navigating the landscape of liver cancer management: Study designs in clinical trials and clinical practice.

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer death worldwide and its prognosis is highly heterogeneous, being related not only to tumour burden but also to the severity of underlying chronic liver disease. Moreover, advances in systemic therapies for HCC have increased the complexity of patient management. Randomised-controlled trials represent the gold standard for evidence generation across all areas of medicine and especially in the oncology field, as they allow for unbiased estimates of treatment effect without confounders. Observational studies have many problems that could reduce their internal and external validity. However, large prospective (well-conducted) observational real-world studies can detect rare adverse events or monitor the occurrence of long-term adverse events. How best to harness real world data, which refers to data generated from the routine care of patients, and real-world 'evidence', which is the evidence generated from real-world data, represents an open challenge. In this review article, we aim to provide an overview of the benefits and limitations of different study designs, particularly focusing on randomised-controlled trials and observational studies, to address important and not fully resolved questions in HCC research.

Insights into the performance of PREDICT tool in a large Mainland Chinese breast cancer cohort: a comparative analysis of versions 3.0 and 2.2.

BACKGROUND: PREDICT is a web-based tool for forecasting breast cancer outcomes. PREDICT version 3.0 was recently released. This study aimed to validate this tool for a large population in mainland China and compare v3.0 with v2.2. METHODS: Women who underwent surgery for nonmetastatic primary invasive breast cancer between 2010 and 2020 from the First Affiliated Hospital of Wenzhou Medical University were selected. Predicted and observed 5-year overall survival (OS) for both v3.0 and v2.2 were compared. Discrimination was compared using receiver-operator curves and DeLong test. Calibration was evaluated using calibration plots and chi-squared test. A difference greater than 5% was deemed clinically relevant. RESULTS: A total of 5424 patients were included, with median follow-up time of 58 months (IQR 38-89 months). Compared to v2.2, v3.0 did not show improved discriminatory accuracy for 5-year OS (AUC: 0.756 vs 0.771), same as ER-positive and ER-negative patients. However, calibration was significantly improved in v3.0, with predicted 5-year OS deviated from observed by -2.0% for the entire cohort, -2.9% for ER-positive and -0.0% for ER-negative patients, compared to -7.3%, -4.7% and -13.7% in v2.2. In v3.0, 5-year OS was underestimated by 9.0% for patients older than 75 years, and 5.8% for patients with micrometastases. Patients with distant metastases postdiagnosis was overestimated by 10.6%. CONCLUSIONS: PREDICT v3.0 reliably predicts 5-year OS for the majority of Chinese patients with breast cancer. PREDICT v3.0 significantly improved the predictive accuracy for ER-negative groups. Furthermore, caution is advised when interpreting 5-year OS for patients aged over 70, those with micrometastases or metastases postdiagnosis.

Estimating scenarios for survival time in patients with advanced melanoma receiving immunotherapy and targeted therapy.

BACKGROUND: We aim to provide survival scenario estimates for patients with advanced melanoma starting targeted therapies and immunotherapies. MATERIALS AND METHODS: We sought randomized trials of targeted therapies and immunotherapies for advanced melanoma and recorded the following percentiles (represented survival scenario) from each overall survival (OS) curve: 90th (worst-case), 75th (lower-typical), 50th (median), 25th (upper-typical), and 10th (best-case). We tested whether these scenarios can be estimated for each OS curve by multiplying its median by 4 multiples: 0.25 (worst-case), 0.5 (lower-typical), 2 (upper-typical), and 3 (best-case). RESULTS: We identified 15 trials with 8025 patients. For first-line combination targeted therapy treatment groups, the median (interquartile range, IQR) in months for each percentile was: 90th, 6.2 (6.0-6.5); 75th, 11.3 (11.3-11.4); and median, 24.4 (23.5-25.3). For the first-line combination immunotherapy treatment group, the percentiles in months were: 90th, 3.9 (2.8-4.5); 75th, 13.4 (10.1-15.4), median 73 (not applicable). In targeted therapy groups, simple multiples of the median OS were accurate for estimating the 90th percentile in 80%; 75th percentile in 40%; 25th percentile in 100%. In immunotherapy groups, these multiples were accurate at 0% for the 90th percentile, and 43% for the 75th percentile. The 90th percentile (worst-case scenario) was better estimated as 1/6× median OS, and the 75th percentile (lower-typical) as 1/3× median OS. CONCLUSIONS: Simple multiples of the median OS are a useful framework to estimate scenarios for survival for patients receiving targeted therapies, not immunotherapy. Longer follow-up is required to estimate upper-typical and best-case scenarios.

Prognostic significance of postoperative serological incomplete conversion of AFP and PIVKA-II after hepatic resection for hepatocellular carcinoma: a multicenter analysis of 1755 patients.

BACKGROUND: The value of serum biomarkers, particularly alpha-fetoprotein (AFP) and protein induced by vitamin K absence or antagonist-II (PIVKA-II), gains increasing attention in prognostic evaluation and recurrence monitoring for patients with hepatocellular carcinoma (HCC). This study investigated the implications of serological incomplete conversion (SIC) of these 2 biomarkers as prognostic indicators for long-term outcomes after HCC resection. METHODS: A multicenter observational study was conducted on a cohort of HCC patients presenting with AFP (>20 ng/mL) or PIVKA-II (>40 mAU/mL) positivity who underwent curative-intent resection. Based on their postoperative AFP and PIVKA-II levels at first postoperative follow-up (4~8 weeks after surgery), these patients were stratified into the serological incomplete conversion (SIC) and serological complete conversion (SCC) groups. The study endpoints were recurrence and overall survival (OS). RESULTS: Among 1755 patients, 379 and 1376 were categorized as having SIC and SCC, respectively. The SIC group exhibited 1- and 5-year OS rates of 67.5% and 26.3%, with the corresponding recurrence rates of 53.2% and 79.0%, respectively; while the SCC group displayed 1- and 5-year OS rates of 95.8% and 62.5%, with the corresponding recurrence rates of 16.8% and 48.8%, respectively (both P < .001). Multivariate Cox regression analysis demonstrated that postoperative SIC was an independent risk factor for both increased recurrence (HR: 2.40, 95% CI, 2.04-2.81, P < .001) and decreased OS (HR: 2.69, 95% CI, 2.24-3.24, P < .001). CONCLUSION: The results emphasize that postoperative incomplete conversion of either AFP or PIVKA-II is a significant prognostic marker, indicating a higher risk for adverse oncologic outcomes following HCC resection. This revelation has crucial implications for refining postoperative adjuvant therapy and surveillance strategies for HCC patients.

Tenofovir is associated with a better prognosis than entecavir for hepatitis B virus-related hepatocellular carcinoma.

BACKGROUND AND AIMS: Whether tenofovir or entecavir has different effects on the prevention of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) in secondary and tertiary preventive settings is still a matter of debate. This study aimed to compare the long-term prognosis of HCC between tenofovir and entecavir in patients with chronic hepatitis B (CHB). METHODS: CHB patients diagnosed with HCC between November 2008 and December 2018 and treated with either entecavir or tenofovir at a tertiary center in Korea were included. The effect of tenofovir compared to entecavir on the prognosis of HBV-related HCC was assessed using multivariable-adjusted Cox and propensity score (PS)-matched analyses. Various predefined subgroup analyses were conducted. RESULTS: During a median follow-up period of 3.0 years, the mortality rate for entecavir-treated patients (n = 3,469) was 41.2%, while tenofovir-treated patients (n = 3,056) had a mortality rate of 34.6%. Overall survival (OS) was better in the tenofovir group (adjusted hazard ratio [aHR], 0.79; P < .001), which were consistently observed in the PS-matched analysis. The magnitude of the risk difference in OS was more prominent 2 years after the diagnosis of HCC (aHR, 0.50; P < .001) than 2 years before (aHR, 0.88; P = .005), and it was more pronounced in patients with earlier HCC stages. In all subgroups, except for those with shorter life expectancy, such as those with compromised liver function, tenofovir was associated with better OS compared to entecavir. CONCLUSIONS: Among patients with HBV-related HCC, those treated with tenofovir had a better prognosis than those treated with entecavir, particularly among those with prolonged survival.

Four-year overall survival update from the phase III HIMALAYA study of tremelimumab plus durvalumab in unresectable hepatocellular carcinoma.

BACKGROUND: In the phase III HIMALAYA study (NCT03298451) in unresectable hepatocellular carcinoma (uHCC), STRIDE (Single Tremelimumab Regular Interval Durvalumab) significantly improved overall survival (OS) versus sorafenib; durvalumab monotherapy was noninferior to sorafenib for OS. Results reported herein are from a 4-year updated OS analysis of HIMALAYA. PATIENTS AND METHODS: Participants with uHCC and no previous systemic treatment were randomized to STRIDE (n = 393), durvalumab (n = 389), or sorafenib (n = 389). The updated data cut-off was 23 January 2023. OS and serious adverse events (AEs) were assessed. Additionally, baseline characteristics and subsequent therapies were analyzed in long-term survivors (≥36 months beyond randomization). RESULTS: For STRIDE, durvalumab, and sorafenib, median [95% confidence interval (CI)] follow-up was 49.12 months (46.95-50.17 months), 48.46 months (46.82-49.81 months), and 47.31 months (45.08-49.15 months), respectively. OS hazard ratio (95% CI) for STRIDE versus sorafenib was 0.78 (0.67-0.92). The 36-month OS rate for STRIDE was 30.7% versus 19.8% for sorafenib. The 48-month OS rate remained higher for STRIDE at 25.2%, versus 15.1% for sorafenib. The long-term OS benefit of STRIDE was observed across clinically relevant subgroups and was further improved in participants who achieved disease control. Long-term survivors with STRIDE (n = 103) included participants across clinically relevant subgroups, and 57.3% (59/103) had no reported subsequent anticancer therapy. No new serious treatment-related AEs occurred with STRIDE from the primary analysis (17.5%; 68/388). Durvalumab maintained OS noninferiority to sorafenib and no late-onset safety signals were identified. CONCLUSIONS: These data represent the longest follow-up to date in phase III studies in uHCC. The unprecedented 3- and 4-year OS rates reinforce the sustained long-term OS benefit of STRIDE versus sorafenib. STRIDE maintained a tolerable yet differentiated safety profile from other current uHCC therapies. Results continue to support the long-term benefits of STRIDE in a diverse population, reflective of uHCC globally.