Distinct Prognostic Groups Research Articles

Pan-cancer characterization of cellular senescence reveals its inter-tumor heterogeneity associated with the tumor microenvironment and prognosis

Cellular senescence (CS) is characterized by the irreversible cell cycle arrest and plays a key role in aging and diseases, such as cancer. Recent years have witnessed the burgeoning exploration of the intricate relationship between CS and cancer, with CS recognized as either a suppressing or promoting factor and officially acknowledged as one of the 14 cancer hallmarks. However, a comprehensive characterization remains absent from elucidating the divergences of this relationship across different cancer types and its involvement in the multi-facets of tumor development. Here we systematically assessed the cellular senescence of over 10,000 tumor samples from 33 cancer types, starting by defining a set of cancer-associated CS signatures and deriving a quantitative metric representing the CS status, called CS score. We then investigated the CS heterogeneity and its intricate relationship with the prognosis, immune infiltration, and therapeutic responses across different cancers. As a result, cellular senescence demonstrated two distinct prognostic groups: the protective group with eleven cancers, such as LIHC, and the risky group with four cancers, including STAD. Subsequent in-depth investigations between these two groups unveiled the potential molecular and cellular mechanisms underlying the distinct effects of cellular senescence, involving the divergent activation of specific pathways and variances in immune cell infiltrations. These results were further supported by the disparate associations of CS status with the responses to immuno- and chemo-therapies observed between the two groups. Overall, our study offers a deeper understanding of inter-tumor heterogeneity of cellular senescence associated with the tumor microenvironment and cancer prognosis.

Profiling hypoxia signaling reveals a lncRNA signature contributing to immunosuppression in high-grade glioma.

Hypoxic conditions in glioma are linked to tumor aggressiveness, poor prognosis, and treatment resistance. Long non-coding RNAs (lncRNAs) play key roles in the hypoxic and immune microenvironment of cancers, but their link to hypoxia-induced immunosuppression in high-grade glioma (HGG) is not well-studied. Gene expression profiles from TCGA and CGGA, along with clinical and genomic data, were analyzed. Bioinformatics methods including Consensus Clustering, Pearson correlation, and Cox regression analyses were used. Cell proliferation was assessed using cell counting kit-8 and colony formation assays. Glioma-macrophage interactions were evaluated using a co-culture model. Hypoxia subtype clustering showed hypoxic stress correlates with worse HGG prognosis. Eight hypoxia-related lncRNAs (AP000695.4, OSMR-AS1, AC078883.3, RP11-545E17.3, LINC01057, LINC01503, TP73-AS1, and LINC00672) with prognostic value were identified, forming a risk signature that separated patients into distinct prognostic groups. Multivariate Cox regression confirmed the signature as an independent prognostic factor. High-risk patients had greater hypoxia, leading to an immunosuppressive environment and immunotherapy resistance via tumor-associated macrophages (TAMs). TP73-AS1 significantly influenced hypoxia-induced TAM infiltration and M2 polarization. We profiled hypoxic stress in HGG and developed an 8-lncRNA hypoxia-related signature predicting patient survival and immunotherapy response, emphasizing its role in hypoxia-induced immunosuppression.

Prognostic and Clinical Significance of the Proliferation Marker MCM7 in Breast Cancer.

Minichromosome maintenance complex component 7 (MCM7) plays an essential role in proliferation and DNA replication of cancer cells. However, the expression and prognostic significance of MCM7 in breast cancer (BC) remain to be defined. In this study, we aimed to evaluate the role of MCM7 in BC. We conducted immunohistochemistry staining of MCM7 in 1,156 operable early-stage BC samples and assessed MCM7 at the transcriptomic levels using publicly available cohorts (n = 13,430). MCM7 expression was evaluated and correlated with clinicopathological parameters including Ki67 labelling index and patient outcome. At the transcriptomic level, there was a significant association between high MCM7 mRNA levels and shorter patient survival in the whole cohort and in luminal BC class but not in the basal-like molecular subtype. High MCM7 protein expression was detected in 43% of patients and was significantly associated with parameters characteristic of aggressive tumour behaviour. MCM7 was independently associated with shorter survival, particularly in oestrogen receptor-positive (luminal) BC. MCM7 stratified luminal tumours with aggressive clinicopathological features into distinct prognostic groups. In endocrine therapy-treated BC patients, high MCM7 was associated with poor outcome, but such association disappeared with administration of adjuvant chemotherapy. Patients with high expression of Ki67 and MCM7 showed worst survival, while patients with double low expression BC showed the best outcome compared with single expression groups. The current findings indicate that MCM7 expression has a prognostic value in BC and can be used to identify luminal BC patients who can benefit from adjuvant chemotherapy.

Clinical utility of a blood based assay for the detection of IDH1.R132H-mutant gliomas

Glioma represents the most common central nervous system neoplasm in adults. Current classification scheme utilizes molecular alterations, particularly IDH1.R132H, to stratify lesions into distinct prognostic groups. Identification of the single nucleotide variant through traditional tissue biopsy assessment poses procedural risks and does not fully reflect the heterogeneous and evolving tumor landscape. Here, we introduce a liquid biopsy assay, mt-IDH1dx. The blood-based test allows minimally invasive detection of tumor-derived extracellular vesicle RNA using only 2 ml plasma volume. We perform rigorous, blinded validation testing across the study population (n = 133), comprising of IDH1.R132H patients (n = 80), IDH1 wild-type gliomas (n = 44), and age matched healthy controls (n = 9). Results from our plasma testing demonstrate an overall sensitivity of 75.0% (95% CI: 64.1%–84.0%), specificity 88.7% (95% CI: 77.0%–95.7%), positive predictive value 90.9%, and negative predictive value 70.1% compared to the tissue gold standard. In addition to fundamental diagnostic applications, the study also highlights the utility of mt-IDH1dx platform for blood-based monitoring and surveillance, offering valuable prognostic information. Finally, the optimized workflow enables rapid and efficient completion of both tumor tissue and plasma testing in under 4 hours from the time of sampling.

Peripheral hemoglobin to albumin ratio predicts prognosis in patients with nasopharyngeal carcinoma underwent concurrent chemoradiotherapy

BackgroundRecently, the hemoglobin to albumin ratio (HAR) has been shown to be closely associated with the survival of certain malignancies. However, its prognostic value in nasopharyngeal carcinoma (NPC) remained to be elucidated. Herein, we aimed to explore the correlation between HAR and overall survival (OS) in NPC patients treated with concurrent chemoradiotherapy (CCRT).MethodsThis retrospective study included a total of 858 patients with NPC receiving CCRT between January 2010 and December 2014 in Sun Yat-sen University Cancer Center. We randomly divided them into the training cohort (N = 602) and the validation cohort (N = 206). We performed univariate and multivariate Cox regression analyses to identify variables associated with OS, based on which, a predictive nomogram was constructed and assessed.ResultsIn both the training and validation cohorts, patients were classified into low- and high-HAR groups according to the cutoff value determined by the maximally selected rank statistics. This HAR cutoff value effectively divided patients into two distinct prognostic groups with significant differences. Multivariable Cox analysis revealed that higher T-stage, N-stage, and HAR values were significantly related to poorer prognosis in NPC patients and served as independent prognostic factors for NPC. Based on these, a predictive model was constructed and graphically presented as a nomogram, whose predictive performance is satisfactory with a C-index of 0.744 [95%CI: 0.679–0.809] and superior to traditional TNM staging system [C-index = 0.609, 95%CI: 0.448–0.770].ConclusionThe HAR value was an independent predictor for NPC patients treated with CCRT, the predictive model based on HAR with superior predictive performance than traditional TNM staging system might improve individualized survival predictions.

Survival Prognostication in Patients with Differentiated Thyroid Cancer and Distant Metastases: A SEER Population-Based Study.

Background: For patients with thyroid cancer, distant metastasis is a significant predictor of poor outcome. Since distant metastasis occurs in less than 10% of patients with differentiated thyroid cancer, correlates of survival in this vulnerable patient population remain understudied. This study aimed to identify prognostic groups among patients with differentiated thyroid cancer and distant metastases and to determine the role of, and interactions between, patient and tumor characteristics in determining survival. Methods: We identified adult patients diagnosed with differentiated thyroid cancer with distant metastases from the U.S. SEER-17 cancer registry (2010-2019). Analyses were performed using Cox proportional hazards regression, survival trees, and random survival forest. Relative importance of patient and tumor factors important for disease-specific and overall survival was assessed based on the random survival forest analyses. Results: Cohort consisted of 2411 patients with differentiated thyroid cancer with distant metastases followed for a median of 62 months. Most common histopathologic subtype (86.0%) was papillary thyroid cancer, and the most common sites of distant metastasis were the lungs (33.7%) and bone (18.9%). Cox proportional hazards model illustrated significant associations between survival and the following: patient age (p < 0.001), tumor size (p < 0.01), and site of distant metastasis (p < 0.05). Survival tree analyses identified three distinct prognostic groups based on disease-specific survival (DSS) (5-year survival of the prognostic groups was 92%, 64%, and 41%; p < 0.001) and four distinct prognostic groups based on overall survival (OS) (5-year survival of the prognostic groups was 96%, 84%, 57%, and 31%; p < 0.001). The first split in the survival trees for DSS and OS was by age at diagnosis (≤57 years vs. ≥58 years) with subsequent splits based on presence/absence of lung metastases, tumor size (≤4 cm vs. >4 cm), and patient age. A total of 558 patients (23.1%) died from thyroid cancer, and 757 patients (31.4%) died from all causes during the study period. Conclusions: This study identifies distinct prognostic groups for patients with differentiated thyroid cancer with distant metastases and highlights the importance of patient age, lung metastases, and tumor size for determining both disease-specific and overall survival. These findings inform risk stratification and treatment decision-making in this understudied patient population.

Conventional and machine learning-based risk scores for patients with early-stage hepatocellular carcinoma.

The performance of machine learning (ML) in predicting the outcomes of patients with hepatocellular carcinoma (HCC) remains uncertain. We aimed to develop risk scores using conventional methods and ML to categorize early-stage HCC patients into distinct prognostic groups. The study retrospectively enrolled 1,411 consecutive treatment-naïve patients with the Barcelona Clinic Liver Cancer (BCLC) stage 0 to A HCC from 2012 to 2021. The patients were randomly divided into a training cohort (n=988) and validation cohort (n=423). Two risk scores (CATS-IF and CATS-INF) were developed to predict overall survival (OS) in the training cohort using the conventional methods (Cox proportional hazards model) and ML-based methods (LASSO Cox regression), respectively. They were then validated and compared in the validation cohort. In the training cohort, factors for the CATS-IF score were selected by the conventional method, including age, curative treatment, single large HCC, serum creatinine and alpha-fetoprotein levels, fibrosis-4 score, lymphocyte-tomonocyte ratio, and albumin-bilirubin grade. The CATS-INF score, determined by ML-based methods, included the above factors and two additional ones (aspartate aminotransferase and prognostic nutritional index). In the validation cohort, both CATS-IF score and CATS-INF score outperformed other modern prognostic scores in predicting OS, with the CATSINF score having the lowest Akaike information criterion value. A calibration plot exhibited good correlation between predicted and observed outcomes for both scores. Both the conventional Cox-based CATS-IF score and ML-based CATS-INF score effectively stratified patients with early-stage HCC into distinct prognostic groups, with the CATS-INF score showing slightly superior performance.

Abstract 2442: Blood based novel mRNA genomic test, for screening, early detection, prognosis and monitoring of prostate cancer using a multi-center study

Abstract Background: Current screening tools, including prostate-specific antigen (PSA) and clinico-pathologic parameters, have limitations in the diagnosis and prognosis of prostate cancer. This study examined whether genomic biomarkers can improve screening and monitoring of prostate cancer. Methods: We identified a panel of 25 prostate cancer-related genes through rigorous bioinformatics, computational analyses and genetic testing. These tests, developed by Geneverify Inc. (Hayward, CA; U.S. patent # 10801072 and 10822661) were utilized and optimized by qRT-PCR to determine the diagnostic and prognostic ability of prostate cancer using blood and tissues. The log2-fold increase in gene expression was used to assign the risk score to individual patients. ROC (receiver operator characteristic), AUC (area under ROC curve), and calibration curves were generated to display the overall performance and discrimination ability to separate cancer and non-cancer specimens. Results: A total of 445 prostate cancer patients (135 blood and 310 tissue samples) and 130 normal samples were analyzed in this study. The eligibility criteria were to collect blood and surgical specimens from patients with prostate cancer. The study endpoints were to analyze mRNA genomic profiling and correlate with clinico-pathologic parameters of the patients. In the blood, a 25-panel gene-set separated prostate cancer patients (n=135) from non-cancer (n=30), AUC = 0.906 [sensitivity = 90% and specificity = 91%]. Assessment of tissue specimens from benign (n=100) and cancer patients (n=310) demonstrated similar results with AUC=0.9514 [sensitivity=95% and specificity=94%]. Interestingly, patients with Gleason grades more than 7 showed higher expression of these genes compared to Gleason Grades less than 7, suggesting the prognostic ability of the gene-set. When we compared the gene expression in blood verses tissues, there were similar patterns, suggesting that blood can be used for screening, diagnosis and risk assessment of prostate cancer. Conclusions: To our knowledge, this is the first study to investigate the role of mRNA-based genomic signatures for screening, early diagnosis and prognosis of prostate cancer using blood samples. Our results suggest that blood mRNA-genomic profiling developed by Geneverify has the ability to diagnose prostate cancer and stratify patients into distinct prognostic groups, which in turn help in making better treatment strategies. Citation Format: Yutaka Hashimoto, Shiv Verma, Guoren Deng, Dharam P. Chauhan, Sujit Nair, Dimple Chakravarty, Hirofumi Yoshino, Junya Arima, Shuichi Tatarano, Yutong Liu, Koji Hatano, Yogesh Shivakumar, Mithua Ghosh, Krishnappa Raghunath, Chitra Chandran, Narasimhan Ragavan, Hideki Enokida, Norio Nonomura, KC Balaji, Sudhir Rawal, Ashutosh Tewari, Rajvir Dahiya, Sanjay Gupta. Blood based novel mRNA genomic test, for screening, early detection, prognosis and monitoring of prostate cancer using a multi-center study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2442.

The clinical, molecular, and prognostic features of the 2022 WHO and ICC classification systems for myelodysplastic neoplasms

Myelodysplastic neoplasms (MDS) are clonal disorders of bone marrow failure exhibiting a variable risk of progression to acute myeloid leukemia. MDS exhibit certain prognostic genetic or cytogenetic abnormalities, an observation that has led to both the pathologic reclassification of MDS in the 2022 World Health Organization (WHO) and International Consensus Classification (ICC) systems, as well as to an updated prognostic schema, the Molecular International Prognostic Scoring System (IPSS-M). This single-institution study characterized the molecular patterns and clinical outcomes associated with the 2022 WHO and ICC classification schemas to assess their clinical utility. Strikingly, with the exception of one individual, all 210 patients in our cohort were classified into analogous categories by the two pathologic/diagnostic schemas. Most patients (70%) were classified morphologically while the remaining 30% had genetically classified disease by both criteria. Prognostic risk, as assessed by the IPSS-M score was highest in patients with MDS with biallelic/multi-hit TP53 mutations and lowest in pts with MDS-SF3B1. Median leukemia-free survival (LFS) was shortest for those with MDS with biallelic/multi-hit TP53 (0.7 years) and longest for those with MDS with low blasts (LFS not reached). These data demonstrate the clear ability of the 2022 WHO and ICC classifications to organize MDS patients into distinct prognostic risk groups and further show that both classification systems share more similarities than differences. Incorporation of the IPSS-M and IPSS-R features provide additive prognostic and survival components to both the WHO and ICC classifications, which together enhance their utility for evaluating and treating MDS patients.

Clinical features associated with epilepsy occurrence, resolution, and drug resistance in children with cerebral palsy: A population-based study.

To investigate clinicoradiological features associated with epilepsy, its resolution, and drug resistance in children with cerebral palsy (CP). Data were gathered from the New South Wales/Australian Capital Territory CP Register, encompassing children with CP born between 2003 and 2015 (n = 1916). Clinical features and the severity of impairments were compared among three groups: children with current epilepsy (n = 604), those with resolved epilepsy by age 5 years (n = 109), and those without epilepsy (n = 1203). Additionally, a subset of the registry cohort attending Children's Hospital Westmead (n = 256) was analysed to compare epilepsy and treatment characteristics between drug-responsive (n = 83) and drug-resistant groups (n = 147) using logistic regression and hierarchical cluster analysis. Manual Ability Classification System levels IV and V, intellectual impairment, and vision impairment were found to be associated with epilepsy in children with CP on multivariable analysis (p < 0.01). Moderate to severe intellectual impairment and bilateral spastic CP were independent positive and negative predictors of epilepsy persistence at the age of 5 years respectively (p < 0.05). Microcephaly and multiple seizure types were predictors of drug-resistant epilepsy (area under the receiver operating characteristic curve of 0.83; 95% confidence interval 0.77-0.9). Children with a known genetic cause (14%) and CP epilepsy surgery group (4.3%) formed specific clinical subgroups in CP epilepsy. Our study highlights important clinical associations of epilepsy, its resolution, and treatment response in children with CP, providing valuable knowledge to aid in counselling families and identifying distinct prognostic groups for effective medical surveillance and optimal treatment. Severe motor and non-motor impairments in cerebral palsy (CP) increase epilepsy risk. Epilepsy more likely resolves in bilateral spastic and milder CP impairments. Epilepsy in CP often manifests at an early age with multiple seizure types and high drug resistance. Children with a known genetic cause and CP epilepsy surgery group represent distinct clinical subgroups.

Metabolomic profile of neuroendocrine tumors identifies methionine, porphyrin, and tryptophan metabolisms as key dysregulated pathways associated with patient survival.

Metabolic profiling is a valuable tool to characterize tumor biology but remains largely unexplored in neuroendocrine tumors (NETs). Our aim was to comprehensively assess the metabolomic profile of NETs and identify novel prognostic biomarkers and dysregulated molecular pathways. Multiplatform untargeted metabolomic profiling (GC-MS, CE-MS, and LC-MS) was performed in plasma from 77 patients with G1-2 extra-pancreatic NETs enrolled in the AXINET trial (NCT01744249) (study cohort) and from 68 non-cancer individuals (control). The prognostic value of each differential metabolite (n = 155) in NET patients (P < .05) was analyzed by univariate and multivariate analyses adjusted for multiple testing and other confounding factors. Related pathways were explored by Metabolite Set Enrichment Analysis (MSEA) and Metabolite Pathway Analysis (MPA). Thirty-four metabolites were significantly associated with progression-free survival (PFS) (n = 16) and/or overall survival (OS) (n = 27). Thirteen metabolites remained significant independent prognostic factors in multivariate analysis, 3 of them with a significant impact on both PFS and OS. Unsupervised clustering of these 3 metabolites stratified patients in 3 distinct prognostic groups (1-year PFS of 71.1%, 47.7%, and 15.4% (P = .012); 5-year OS of 69.7%, 32.5%, and 27.7% (P = .003), respectively). The MSEA and MPA of the 13-metablolite signature identified methionine, porphyrin, and tryptophan metabolisms as the 3 most relevant dysregulated pathways associated with the prognosis of NETs. We identified a metabolomic signature that improves prognostic stratification of NET patients beyond classical prognostic factors for clinical decisions. The enriched metabolic pathways identified reveal novel tumor vulnerabilities that may foster the development of new therapeutic strategies for these patients.

Identifying individualized prognostic signature and unraveling the molecular mechanism of recurrence in early-onset colorectal cancer

BackgroundThe incidence and mortality of early-onset colorectal cancer (EOCRC; < 50 years old) is increasing worldwide, with a high recurrence rate. The inherent heterogeneity of EOCRC makes its treatment challenging. Hence, to further understand the biology and reveal the molecular mechanisms of EOCRC, a recurrence risk signature is needed to guide clinical management.MethodsBased on the relative expression orderings (REOs) of genes in each sample, a prognostic signature was developed and validated utilizing multiple independent datasets. The underlying molecular mechanisms between distinct prognostic groups were explored via integrative analysis of multi-omics data.ResultsThe prognostic signature consisting of 6 gene pairs (6-GPS) could predict the recurrence risk for EOCRC at the individual level. High-risk EOCRC classified by 6-GPS showed a poor prognosis but a good response to adjuvant chemotherapy. Moreover, high-risk EOCRC was characterized by epithelial-mesenchymal transition (EMT) and enriched angiogenesis, and had higher mutation burden, immune cell infiltration, and PD-1/PD-L1 expression. Furthermore, we identified four genes associated with relapse-free survival in EOCRC, including SERPINE1, PECAM1, CDH1, and ANXA1. They were consistently differentially expressed at the transcriptome and proteome levels between high-risk and low-risk EOCRCs. They were also involved in regulating cancer progression and immune microenvironment in EOCRC. Notably, the expression of SERPINE1 and ANXA1 positively correlated with M2-like macrophage infiltration.ConclusionOur results indicate that 6-GPS can robustly predict the recurrence risk of EOCRC, and that SERPINE1, PECAM1, CDH1, and ANXA1 may serve as potential therapeutic targets. This study provides valuable information for the precision treatment of EOCRC.

Low Levels of Circulating Tumor Cells Correlate with Favorable Clinical Outcome and Unique Biological Features in Newly Diagnosed Multiple Myeloma Patients

Introduction Circulating tumor cells (CTCs) have been proposed as a prognostic biomarker in newly-diagnosed MM (NDMM) but their low frequency questions their use in clinical practice. Lower CTC levels (cut-off &amp;lt;0.01-0.07%) correlate with a favorable prognostic outcomes in transplant-eligible (TE) patients (pts); however, several issues remain to be addressed. On clinical grounds, it remains unclear whether there is a similar prognostic cut-off value for transplant-ineligible (TI) pts. Furthermore, it is not clear whether the CTCs mimic the characteristics of a single (main)-site bone marrow (ΒΜ) myeloma cells or if they represent the total disease burden, i.e. in cases with extramedullary or macrofocal disease. Moreover, there is limited information of the biological factors that may lead myeloma cells to egress their primary BM site. Methods BM and matched peripheral blood (PB) samples from 550 NDMM pts (210 TE, 340 TI) were evaluated with NGF (median LOD 2.1x10 -6) for the presence of myeloma cells. Various multivariable regression models including CTCs, R-ISS, cytogenetic status and LDH were assessed to define the optimal clinical CTC cut-off. The BM niche profiling was examined with mass cytometry (CyTOF, n=15 pts, 8 with no CTCs, 7 with CTCs higher than the cut-off) and various multicolor flow cytometry panels (n=199 pts including 56 pts with no CTCs) that allowed the detection of 32 distinct immune populations. Results The median value of CTCs was 0.01% of total PB cells (range: 0.0002%-63%) and in 57/550 (10.4%) pts CTCs could not be detected. Increased levels of CTCs correlated with ISS III stage (median: 0.037%, 0.007% and 0.002% for pts with ISS-3, ISS-2 and ISS-1, respectively; p&amp;lt;0.0001), high risk cytogenetics (median: 0.038% vs. 0.006% in standard risk, p&amp;lt;0.0001), and higher levels of b2-microglobulin and BM infiltration. Median follow-up was 41 months (range: 5-66 months). PFS and OS were gradually worsened towards a CTCs log increment, independently of ISS, cytogenetic status and LDH. Hence, pts with undetectable CTCs had the most favorable prognosis with a 5-year PFS and OS of 83% and 97% respectively. The optimal clinical CTCs cut-off that stratified pts into two distinct prognostic groups was defined at the level of 0.02%, which was common for both TE (median PFS: NR in both high and low CTC subsets; p&amp;lt;0.01) and TI subgroups (median PFS: 47 for low vs. 23 months for high CTCs subset, p&amp;lt;0.0001). Importantly, this cut-off, together with the phenotypic classification of pts (MGUS-like, MM-like etc.) could be incorporated in the established R-ISS system, providing an improved ptnts' stratification. The 2-year achievement of MRD negativity was 45%, 67% and 73% for pts with high, low and undetectable CTCs and median time for MRD negativity was 34, 17 and 12 months, respectively (p&amp;lt;0.001). Of note, pts with high CTCs who achieved MRD negativity, modulated their unfavorable risk status and showed similar PFS with those who had low CTCs. In 73/493 (14.8%) pts with detectable CTCs, there was an obvious phenotypic inconsistency between BM myeloma cells and CTCs, either in regard to the relative ratio of the detected (sub)clones, or the appearance of ≥1 phenotypically distinct clonal populations, which were present only in BM or PB. Pts with phenotypic inconsistencies had higher CTC levels and more often diffuse MRI patterns than those with a phenotypic agreement (frequency: 40% vs. 10%; p&amp;lt;0.01). To better understand the heterogeneous dissemination of myeloma cells to PB, we compared the BM niche profiles of pts with high CTC levels (&amp;gt;10 -3) and those with no CTCs. The analyses highlighted clear differences in the BM composition of the two groups with the BM of pts with no CTCs showing significantly lower levels of T cells, NK cells, TAMs and an increased naïve/memory B cell ratio. Of note, no differences were observed in the prevalence of immunosuppressive cell subsets (Tregs, MDSCs) between the two groups. Discussion The presence of CTCs at levels &amp;gt;0.02% confers an adverse prognostic factor for NDMM pts, irrespective of their transplant status. On the contrary, pts with no CTCs have the more favorable outcome and share unique microenvironmental features, which may eliminate CTCs dissemination. Since the liquid biopsy seems to be a better representative of the entire tumor load than a single tissue biopsy, the CTC analysis serves as the new hallmark for the real-time evaluation of a patient's disease and immune status.

Machine-Based Learning Hierarchical Cluster Analysis: Sex-Based Differences in Prognosis Following Resection of Hepatocellular Carcinoma.

Patients with hepatocellular carcinoma (HCC) may have a heterogeneous presentation, as well as different long-term outcomes following surgical resection. We sought to use machine learning to cluster patients into different prognostic groups based on preoperative characteristics. Patients who underwent curative-intent liver resection for HCC between 2000 and 2020 were identified from a large international multi-institutional database. A hierarchical cluster analysis was performed based on preoperative factors to characterize patterns of presentation and define disease-free survival (DFS). Among 966 with HCC, 3 distinct clusters were identified: Cluster 1 (n = 160, 16.5%), Cluster 2 (n = 537, 55.6%) and Cluster 3 (n = 269, 27.8%). Cluster 1 (n = 160, 16.5%) consisted of female patients (n = 160, 100%), low inflammation-based scores, intermediate tumor burden score (TBS) (median: 4.71) and high alpha-fetoprotein (AFP) levels (median 41.3ng/mL); Cluster 2 consisted of male individuals (n = 537, 100%), mainly with a history of HBV infection (n = 429, 79.9%), low inflammation-based scores, intermediate AFP levels (median 26.0ng/mL) and lower TBS (median 4.49); Cluster 3 was comprised of older patients (median age 68years) predominantly male (n = 248, 92.2%) who had low incidence of HBV/HCV infection (7.1% and 8.2%, respectively), intermediate AFP levels (median 16.8ng/mL), high inflammation-based scores and high TBS (median 6.58). Median DFS worsened incrementally among the three different clusters with Cluster 3 having the lowest DFS (Cluster 1: median not reached; Cluster 2: 34months, 95% CI 23.0-48.0, Cluster 3: 19months, 95% CI 15.0-29.0, p < 0.05). Cluster analysis classified HCC patients into three distinct prognostic groups. Cluster assignment predicted DFS following resection of HCC with the female cluster having the most favorable prognosis following HCC resection.

Multi-Institutional Validation of the Recursive Partitioning Analysis for Overall Survival in Patients Undergoing Spine Radiosurgery for Spine Metastasis

The recently published spine radiosurgery (sSRS) recursive partitioning analysis (RPA) for overall survival (OS) separated patients into 3 distinct prognostic groups. We sought to externally validate this RPA using 3 separate multi-institutional datasets. A total of 444 patients were utilized to develop the recently published sSRS RPA predictive of OS in patients with spine metastases. The RPA identified three distinct prognostic classes. RPA Class 1 was defined as KPS >70 and controlled systemic disease (n = 142); RPA Class 2 was defined as KPS>70 with uncontrolled systemic disease or KPS ≤70, age ≥54 and absence of visceral metastases (n = 207); RPA Class 3 was defined as KPS ≤70 and age <54 years or KPS≤70, age ≥54 years and presence of visceral metastases (n = 95). We utilized data from 3 large tertiary care centers to independently validate this RPA. Data from each institution was utilized independently to validate the RPA to minimize confounding based on institutional differences in patient selection. A total of 1,184 patients (221 patients from institution A, 749 institution B, and 214 from institution C) were in the validation cohort and were divided based on their RPA Class. Kaplan-Meier method was used to estimate OS and log-rank test was used to compare OS between RPA classes. In each of the validation cohorts, the median OS was 19.9 months (institution A), 11.0 months (institution B), and 24.4 months (institution C). The patient distribution into RPA classification based on Institution A/B/C was, Class 1 (19.4%, 15.1%, 50.5%), Class 2 (74.7%, 57.7%%, 37.9%), and Class 3 (5.9%, 27.2%%, 11.2%), respectively. The median OS for patients in the validation cohort at Institution A/B/C based on RPA class was Class 1 (54 months, 27.1 months, 50.0 months), Class 2 (15.9 months, 13.0 months, 15.1 months) and Class 3 (6.9 months, 3.5 months, 6.1 months), respectively. Patients in RPA Class 1 had a significantly better OS compared to those in Class 2 of the each of the three external institution validation cohorts (p<0.01). Similarly, patients in RPA Class 2 had a significantly better OS compared to those in Class 3 (p<0.01). The external datasets from three large institutions independently validated the spine SRS RPA successfully for OS in patients undergoing sSRS for spinal metastases. This is the first RPA for OS to have been externally validated using multiple large datasets. Based on this validation, upfront spine SRS is strongly supported for patients in RPA Class 1 and Class 2 and is also cost effective with median OS >11 months for these patients. Patients in RPA Class 3 would benefit most from upfront conventional radiotherapy given their poor expected survival. Given successful external validation, this RPA helps guide physicians to identify those patients with spinal metastases who most benefit from sSRS.

Prognostic role of the number of resected and negative lymph nodes in Spanish patients with gastric cancer

IntroductionLymph node (LN) involvement is one of the most critical prognostic factors in resected gastric cancer (GC). Some analyses, mainly conducted in Asian populations, have found that patients with a higher number of total lymph nodes (NTLN) and/or negative lymph nodes (NNLN) have a better prognosis, although other authors have failed to confirm these results. Materials and methodsRetrospective study including all patients with GC resected in a tertiary hospital in Spain between 2001 and 2019 (n = 315). Clinicopathological features were collected and patients were categorized according to the NTLN and the NNLN. Statistical analyses were performed. ResultsMean NNLN was 17. The NNLN was significantly related to multiple clinicopathological variables, including recurrence and tumor-related death. The classification based on the NNLN (N1: ≥16, N2: 8–15, N3: ≤7) effectively stratified the entire cohort into three distinct prognostic groups and maintained its prognostic value within both the pN0 and pN+ patient subsets. Furthermore, it was an independent prognostic indicator for both overall and disease-free survival. Conversely, the mean NTLN was 21.9. Patients with ≤16 LN retrieved exhibited distinct clinicopathological features compared to those with >16 LN, but no significant differences were observed in terms of recurrence or disease-associated death. The application of alternative cut-off points for NTLN (10, 20, 25, 30, and 40) showed no prognostic significance. ConclusionsIn Spanish patients with resected GC the NNLN hold prognostic significance, while the NTLN does not appear to be prognostically significant. Incorporating the NNLN into GC staging may enhance the accuracy of the TNM system.

A threshold for mitotic activity and post-surgical residual volume defines distinct prognostic groups for astrocytoma IDH-mutant.

The distinction between CNS WHO grade 2 and grade 3 is instrumental in choosing between observational follow-up and adjuvant treatment for resected astrocytomas IDH-mutant. However, the criteria of CNS WHO grade 2 versus 3 have not been updated since the pre-IDH era. Maximal mitotic activity in consecutive high-power fields corresponding to 3 mm2 was examined for 118 lower-grade astrocytomas IDH-mutant. The prognostic value for time-to-treatment (TTT) and overall survival (OS) of mitotic activity and other putative prognostic factors (including age, performance status, pre-surgical tumour volume, multilobar involvement, post-surgical residual tumour volume, midline involvement) was assessed for tumours with ATRX loss and the absence of CDKN2A homozygous deletion or CDK4 amplification, contrast enhancement, histological necrosis, and microvascular proliferation. Seventy-one per cent of the samples had < 6 mitoses per 3 mm2 . Mitotic activity, residual volume, and multilobar involvement were independent prognostic factors of TTT. The threshold of ≥ 6 mitoses per 3 mm2 identified patients with a shorter TTT (median 18.5 months). A residual volume ≥ 1 cm3 also identified patients with a shorter TTT (median 24.5 months). The group defined by < 6 mitoses per 3 mm2 and a residual volume < 1 cm3 had the longest TTT (median 73 months) and OS (100% survival at 7 years). These findings were confirmed in a validation cohort of 52 tumours. Mitotic activity and post-surgical residual volume can be combined to evaluate the prognosis for patients with resected astrocytomas IDH-mutant. Patients with < 6 mitoses per 3 mm2 and a residual volume < 1 cm3 were the best candidates for observational follow-up.

Estimating survival in patients with melanoma brain metastases: prognostic value of lactate dehydrogenase.

Patients with melanoma brain metastases (MBM) have poor prognosis, albeit advances in locoregional and systemic treatments. The melanoma-specific Graded Prognostic Assessment (GPA) effectively stratifies survival for patients with MBM. Nevertheless, lactate dehydrogenase (LDH), a well known prognostic factor for patients with melanoma, is not represented in the GPA scores and might add prognostic information for patients with MBM. In this study, 150 consecutive patients with MBM were retrospectively analyzed with the aim of evaluating independent prognostic factors for MBM patients, including LDH. Furthermore, we implemented a disease-specific prognostic score and estimated survival according to treatment modalities. On the basis of multivariable Cox regression analyses, six prognostic factors (age, BRAF status, number of MBM, number of extracranial metastatic sites, performance status, and LDH level) resulted statistically significant in terms of survival and were combined in a prognostic score to stratify patients in distinct prognostic groups ( P < 0.0001). Among treatment modalities, a multimodal approach with stereotactic radiosurgery or neurosurgery associated with systemic therapy showed the best outcome (median overall survival: 12.32 months, 95% confidence interval, 7.92-25.30). This is the first study to demonstrate that LDH has independent prognostic value for patients with MBM and might be used to improve prognostic stratification, albeit external validation is mandatory. Survival of patients with MBM is affected by both disease-specific risk factors and treatment modalities, with locoregional treatments associated with better outcomes.

Integrated Pathologic Score Effectively Stratifies Patients With Pancreatic Ductal Adenocarcinoma Who Received Neoadjuvant Therapy and Pancreaticoduodenectomy.

Neoadjuvant therapy is increasingly used to treat patients with pancreatic ductal adenocarcinoma (PDAC). Pathologic parameters of treated PDAC, including tumor (ypT) and lymph node (ypN) stage, and tumor response grading (TRG) are important prognostic factors in this group of patients. To our knowledge, a multifactorial prognostic score combining pathologic features including ypT, ypN, and TRG in treated PDAC patients has not been reported. Our cohort consisted of 398 PDAC patients who received neoadjuvant therapy and underwent pancreaticoduodenectomy at our institution. All pancreaticoduodenectomy specimens were grossly and microscopically evaluated using a standard protocol. The integrated pathologic score (IPS) was calculated as the sum of the scores for ypT, ypN, and TRG according to either the MD Anderson grading system (IPSMDA) or the College of American Pathologists (CAP) grading system (IPSCAP). The IPSMDA and IPSCAP were correlated with clinicopathologic parameters and patient survival. Using either IPSMDA or IPSCAP, PDAC patients were stratified into 3 distinct prognostic groups for both disease-free survival (DFS) ( P <0.001) and overall survival (OS) ( P <0.001). The IPSMDA and IPSCAP correlated with tumor differentiation, margin status, the American Joint Committee on Cancer (AJCC) stage, and tumor recurrence ( P <0.05). In multivariate analysis, IPSMDA, IPSCAP, margin status, and tumor differentiation were independent prognostic factors for both DFS ( P <0.05) and OS ( P <0.05). However, patients with AJCC stage IB, IIA, or IIB disease had no significant difference in either DFS or OS ( P >0.05). The IPS appears to provide improved prognostic information compared with AJCC staging for preoperatively treated patients with PDAC.

The clinical value of progesterone receptor expression in luminal breast cancer: A study of a large cohort with long-term follow-up.

The routine assessment of progesterone receptor (PR) expression in breast cancer (BC) remains controversial. This study aimed to evaluate the role of PR expression in luminal BC, with emphasis on the definition of positivity and its prognostic significance as compared to Ki67 expression. A large cohort (n=1924) of estrogen receptor (ER)-positive/HER2-negative BC was included. PR was immunohistochemically (IHC) stained on full face sections and core needle biopsies (CNB) where the optimal scoring cutoff was evaluated. In addition, the association of PR with other clinicopathological factors, cellular proliferation, disease outcome, and response to adjuvant therapy were analyzed. Although several cutoffs showed prognostic significance, the optimal cutoff to categorize PR expression into two clinically distinct prognostic groups on CNB was 10%. PR negativity showed a significant association with features of aggressive tumor behavior and poor outcome. Multivariate analyses indicated that the association between PR negativity and poor outcome was independent of tumor grade, size, node stage, and Ki67. PR negativity showed independent association with shorter survival in patients who received endocrine therapy whereas Ki67did not. PR IHC expression provides independent prognostic value superior to Ki67. Routine assessment of PR expression in BC using 10% cutoff in the clinical setting is recommended. In this study, we have established an optimal approach to determine the prognostic value of progesterone receptor expression in estrogen receptor-positive breast cancer patients. To do this, the levels of progesterone receptor were measured in a large cohort of estrogen receptor-positive breast cancer patients. We have refined the definition of progesterone receptor positivity in estrogen receptor-positive breast cancer. We show that progesterone receptor expression adds prognostic and predictive value of endocrine therapy in estrogen receptor-positive breast cancer patients, and our results show that the absence of progesterone receptor is associated with poorer outcomes independent of tumor grade, size, node stage, and Ki67 expression.