Prognostic Classification Research Articles

Exploring the accuracy of tooth loss prediction between a clinical periodontal prognostic system and a machine learning prognostic model.

The aim of this analysis was to compare a clinical periodontal prognostic system and a developed and externally validated artificial intelligence (AI)-based model for the prediction of tooth loss in periodontitis patients under supportive periodontal care (SPC) for 10 years. Clinical and radiographic parameters were analysed to assign tooth prognosis with a tooth prognostic system (TPS) by two calibrated examiners from different clinical centres (London and Pittsburgh). The prediction model was developed on the London dataset. A logistic regression model (LR) and a neural network model (NN) were developed to analyse the data. These models were externally validated on the Pittsburgh dataset. The primary outcome was 10-year tooth loss in teeth assigned with 'unfavourable' prognosis. A total of 1626 teeth in 69 patients were included in the London cohort (development cohort), while 2792 teeth in 116 patients were included in the Pittsburgh cohort (external validated dataset). While the TPS in the validation cohort exhibited high specificity (99.96%), moderate positive predictive value (PPV = 50.0%) and very low sensitivity (0.85%), the AI-based model showed moderate specificity (NN = 52.26%, LR = 67.59%), high sensitivity (NN = 98.29%, LR = 91.45%), and high PPV (NN = 89.1%, LR = 88.6%). AI-based models showed comparable results with the clinical prediction model, with a better performance in specific prognostic risk categories, confirming AI prediction model as a promising tool for the prediction of tooth loss.

Identification of histopathological classification and establishment of prognostic indicators of gastric adenocarcinoma based on deep learning algorithm.

The aim of this study is to establish a deep learning (DL) model to predict the pathological type of gastric adenocarcinoma cancer based on whole-slide images(WSIs). We downloaded 356 histopathological images of gastric adenocarcinoma (STAD) patients from The Cancer Genome Atlas database and randomly divided them into the training set, validation set and test set (8:1:1). Additionally, 80 H&E-stained WSIs of STAD were collected for external validation. The CLAM tool was used to cut the WSIs and further construct the model by DL algorithm, achieving an accuracy of over 90% in identifying and predicting histopathological subtypes. External validation results demonstrated the model had a certain generalization ability. Moreover, DL features were extracted from the model to further investigate the differences in immune infiltration and patient prognosis between the two subtypes. The DL model can accurately predict the pathological classification of STAD patients, and provide certain reference value for clinical diagnosis. The nomogram combining DL-signature, gene-signature and clinical features can be used as a prognostic classifier for clinical decision-making and treatment.

Nomograms for prognosis prediction in esophageal adenocarcinoma: realities and challenges.

Prognostic assessment is of great significance for individualized treatment and care of cancer patients. Although the TNM staging system is widely used as the primary prognostic classifier for solid tumors in clinical practice, the complexity of tumor occurrence and development requires more personalized probability prediction models than an ordered staging system. By integrating clinical, pathological, and molecular factors into digital models through LASSO and Cox regression, a nomogram could provide more accurate personalized survival estimates, helping clinicians and patients develop more appropriate treatment and care plans. Esophageal adenocarcinoma (EAC) is a common pathological subtype of esophageal cancer with poor prognosis. Here, we screened and comprehensively reviewed the studies on EAC nomograms for prognostic prediction, focusing on performance evaluation and potential prognostic factors affecting survival. By analyzing the strengths and limitations of the existing nomograms, this study aims to provide assistance in constructing high-quality prognostic models for EAC patients.

15-Gene Expression Profile and PRAME as Integrated Prognostic Test for Uveal Melanoma: First Report of Collaborative Ocular Oncology Group Study No. 2 (COOG2.1).

Validated and accurate prognostic testing is critical for precision medicine in uveal melanoma (UM). Our aims were to (1) prospectively validate an integrated prognostic classifier combining a 15-gene expression profile (15-GEP) and PRAME RNA expression and (2) identify clinical variables that enhance the prognostic accuracy of the 15-GEP/PRAME classifier. This study included 1,577 patients with UM of the choroid and/or ciliary body who were enrolled in the Collaborative Ocular Oncology Group Study Number 2 (COOG2) and prospectively monitored across 26 North American centers. Test results for 15-GEP (class 1 or class 2) and PRAME expression status (negative or positive) were available for all patients. The primary end point was metastasis-free survival (MFS). 15-GEP was class 1 in 1,082 (68.6%) and class 2 in 495 (31.4%) patients. PRAME status was negative in 1,106 (70.1%) and positive in 471 (29.9%) patients. Five-year MFS was 95.6% (95% CI, 93.9 to 97.4) for class 1/PRAME(-), 80.6% (95% CI, 73.9 to 87.9) for class 1/PRAME(+), 58.3% (95% CI, 51.1 to 66.4) for class 2/PRAME(-), and 44.8% (95% CI, 37.9 to 52.8) for class 2/PRAME(+). By multivariable Cox proportional hazards analysis, 15-GEP was the most important independent predictor of MFS (hazard ratio [HR], 5.95 [95% CI, 4.43 to 7.99]; P < .001), followed by PRAME status (HR, 1.82 [95% CI, 1.42 to 2.33]; P < .001). The only clinical variable demonstrating additional prognostic value was tumor diameter. In the largest prospective multicenter prognostic biomarker study performed to date in UM to our knowledge, the COOG2 study validated the superior prognostic accuracy of the integrated 15-GEP/PRAME classifier over 15-GEP alone and clinical prognostic variables. Tumor diameter was found to be the only clinical variable to provide additional prognostic information. This prognostic classifier provides an advanced resource for risk-adjusted metastatic surveillance and adjuvant trial stratification in patients with UM.

The potential of cancer stem cells for personalized risk assessment and therapeutic intervention in individuals with intrahepatic cholangiocarcinoma

BackgroundAccumulating evidence suggests that intrahepatic cholangiocarcinoma (ICC) is a stem cell-based disease, but information on the biology of cancer stem cells (CSC) in ICC is very limited.MethodsICC RNA-seq cohorts from three different public databases were integrated and the protein-coding genes were divided into different modules using "WGCNA" to screen the most relevant modules with CSC scores. Least Absolute Shrinkage and Selection Operator (LASSO) regression were introduced to construct prognostic classification models. In addition, the extent of immune cell infiltration in patients in different risk groups was assessed based on the ESTIMATE, CIBERSORT, MCP-Counter, and single sample gene set enrichment analysis (ssGSEA) algorithms. Finally, the correlation between different risk scores and common drugs was analyzed by pRRophetic package and Spearman method.ResultsIn the present study, we found that a high CSC score was associated with a poorer prognosis in patients with ICC. The yellow module obtained by WGCNA was significantly positively correlated with the CSCs score, in which 8 genes were served to build a prognostic classification model, and the obtained risk score was negatively correlated with CSCs score and prognosis. The low-risk score was more suitable for immunotherapy, and the high-risk score was more suitable for treatment with 11 antitumor drugs.ConclusionThis study revealed the regulatory role of CSC-mediated EMT, angiogenesis, and immunomodulatory biological processes in ICC, and applied a prognostic classification model to highlight the great potential of CSC for personalized risk assessment, chemotherapy, and immunotherapy intervention in ICC individuals.

P53 Immunohistochemistry Defines a Subset of Human Papillomavirus-Independent Penile Squamous Cell Carcinomas With Adverse Prognosis.

Penile squamous cell carcinoma (PSCC) is classified into 2 prognostically distinct types: human papillomavirus (HPV)-associated and HPV-independent. However, the impact of p53 status on prognosis remains controversial. We correlated HPV and p53 status with the prognosis of a large series of patients with PSCC. p53 was analyzed according to a recently described immunohistochemical (IHC) pattern-based framework that includes 2 normal and 4 abnormal patterns and closely correlates with TP53 mutational status. A total of 122 patients with surgically treated PSCC in 3 hospitals were included. Based on HPV in situ hybridization and p16 and p53 IHC, the tumors were classified into 3 subtypes: HPV-associated, HPV-independent/p53 normal, and HPV-independent/p53 abnormal. All patients were followed up for at least 22 months (median: 56.9 months). Thirty-six tumors (29%) were HPV-associated, 35 (29%) were HPV-independent/p53 normal, and 51 (42%) were HPV-independent/p53 abnormal. Disease-related deaths were observed in 3/36 (8%), 0/35 (0%) and 14/51 (27%) of the patients, respectively (P< 0.001). A total of 7/14 deaths in the latter group were patients with tumors showing p53 abnormal patterns not recognized in the classic p53 IHC interpretation (basal, null, and cytoplasmic). According to our multivariate analysis, HPV-independent/p53 abnormal tumors and advanced stage were associated with impaired disease-specific survival (hazard ratio = 23.4, 95% CI = 2.7-3095.3; P= 0.001 and 16.3, 95% CI = 1.8-2151.5; P= 0.008, respectively). In conclusion, compared with patients with HPV-associated and HPV-independent/p53-normal PSCC, patients with HPV-independent/p53 abnormal PSCC have worse clinical outcomes. p53 IHC results define 2 prognostic categories in HPV-independent PSCC: HPV-independent/p53-normal tumors as low-risk tumors, whereas HPV-independent/p53-abnormal tumors as aggressive neoplasms.

Subunit-specific analysis of cohesin-mutant myeloid malignancies reveals distinct ontogeny and outcomes

Mutations in the cohesin complex components (STAG2, RAD21, SMC1A, SMC3, and PDS5B) are recurrent genetic drivers in myelodysplastic neoplasm (MDS) and acute myeloid leukemia (AML). Whether the different cohesin subunit mutations share clinical characteristics and prognostic significance is not known. We analyzed 790 cohesin-mutant patients from the Dana-Farber Cancer Institute (DFCI) and the Munich Leukemia Laboratory (MLL), 390 of which had available outcome data, and identified subunit-specific clinical, prognostic, and genetic characteristics suggestive of distinct ontogenies. We found that STAG2 mutations are acquired at MDS stage and are associated with secondary AML, adverse prognosis, and co-occurrence of secondary AML-type mutations. In contrast, mutations in RAD21, SMC1A and SMC3 share features with de novo AML with better prognosis, and co-occurrence with de novo AML-type lesions. The findings show the heterogeneous nature of cohesin complex mutations, and inform clinical and prognostic classification, as well as distinct biology of the cohesin complex.

Efficacy and safety of direct oral anticoagulants versus warfarin in the treatment of cerebral venous sinus thrombosis.

Given the evolving application and promising outcomes of direct oral anticoagulants (DOACs) in various thromboembolic conditions, we aimed to compare the efficacy and safety of DOACs with warfarin in the post-acute treatment of cerebral venous sinus thrombosis (CVST) using clinical and radiological parameters. A total of 140 CVST patients were enrolled, with 95 receiving warfarin and 45 receiving DOACs as post-acute treatment. Clinical and imaging parameters of the patients in follow-up visits were investigated, including the last modified Rankin Scale (mRS), venousthromboembolic events, CVST recurrence, mortality rate, recanalization status, and hemorrhagic events, to compare the efficacy and safety of treatment between the two groups. At baseline, patients' assessments using two prognostic scores, ISCVT-RS and IN-REvASC, revealed that there was no statistically significant difference in the distribution of prognostic risk categories between the warfarin and DOACs groups. Following acute therapy, patients in the warfarin and DOACs groups were followedup forthemedian of359 and325days, respectively. Analysis to compare the efficacy of warfarin and DOACs revealed no significant difference in last mRS scores, CVST recurrencerate, venousthromboembolic events, and recanalizationstatus between the two groups. Additionally, there was no statistically significant difference in the risk of hemorrhagic events between warfarin and DOACsgroups. Our findings show that DOACs have comparable safety and efficacy in the post-acute treatment of CVST patients; however, large-scalerandomized controlled trials are required to validate our findings.

Patient-specific computational models predict prognosis in B cell lymphoma by quantifying pro-proliferative and anti-apoptotic signatures from genetic sequencing data

Genetic heterogeneity and co-occurring driver mutations impact clinical outcomes in blood cancers, but predicting the emergent effect of co-occurring mutations that impact multiple complex and interacting signalling networks is challenging. Here, we used mathematical models to predict the impact of co-occurring mutations on cellular signalling and cell fates in diffuse large B cell lymphoma and multiple myeloma. Simulations predicted adverse impact on clinical prognosis when combinations of mutations induced both anti-apoptotic (AA) and pro-proliferative (PP) signalling. We integrated patient-specific mutational profiles into personalised lymphoma models, and identified patients characterised by simultaneous upregulation of anti-apoptotic and pro-proliferative (AAPP) signalling in all genomic and cell-of-origin classifications (8-25% of patients). In a discovery cohort and two validation cohorts, patients with upregulation of neither, one (AA or PP), or both (AAPP) signalling states had good, intermediate and poor prognosis respectively. Combining AAPP signalling with genetic or clinical prognostic predictors reliably stratified patients into striking prognostic categories. AAPP patients in poor prognosis genetic clusters had 7.8 months median overall survival, while patients lacking both features had 90% overall survival at 120 months in a validation cohort. Personalised computational models enable identification of novel risk-stratified patient subgroups, providing a valuable tool for future risk-adapted clinical trials.

SEOM-GG clinical guidelines for the management of germ-cell testicular cancer (2023)

Testicular germ cell tumors are the most common tumors in adolescent and young men. They are curable malignancies that should be treated with curative intent, minimizing acute and long-term side effects. Inguinal orchiectomy is the main diagnostic procedure, and is also curative for most localized tumors, while patients with unfavorable risk factors for recurrence, or those who are unable or unwilling to undergo close follow-up, may require adjuvant treatment. Patients with persistent markers after orchiectomy or advanced disease at diagnosis should be staged and classified according to the IGCCCG prognostic classification. BEP is the most recommended chemotherapy, but other schedules such as EP or VIP may be used to avoid bleomycin in some patients. Efforts should be made to avoid unnecessary delays and dose reductions wherever possible. Insufficient marker decline after each cycle is associated with poor prognosis. Management of residual masses after chemotherapy differs between patients with seminoma and non-seminoma tumors. Patients at high risk of relapse, those with refractory tumors, or those who relapse after chemotherapy should be managed by multidisciplinary teams in experienced centers. Salvage treatment for these patients includes conventional-dose chemotherapy (TIP) and/or high-dose chemotherapy, although the best regimen and strategy for each subgroup of patients is not yet well established. In late recurrences, early complete surgical resection should be performed when feasible. Given the high cure rate of TGCT, oncologists should work with patients to prevent and identify potential long-term side effects of the treatment. The above recommendations also apply to extragonadal retroperitoneal and mediastinal tumors.

The inguinal lymph nodes as regional lymph nodes in anal canal adenocarcinomas: a nationwide database analysis in Japan.

To establish if it is appropriate to treat the inguinal lymph node (LN) of anal canal adenocarcinoma (ACA) as the intermediate LN according to the Japanese classification. The characteristics of 346 ACA patients were examined from the nationwide registry. The effect of LN dissection was evaluated using the therapeutic value index (TVI). Furthermore, the prognostic classification ability of N factors and stage was evaluated using Akaike's information criterion (AIC), the concordance index (C-index), and the 5-year overall survival (OS) rate. The rate of metastasis of the inguinal LN was 7.5% and the TVI was 3.05. Evaluation using AIC and the C-index showed better results when the inguinal LN was treated as the intermediate LN. The 5-year OS rate for 66 patients with perirectal or intermediate LN metastasis, 7 with inguinal LN metastasis, and 13 with inguinal and perirectal or intermediate LN metastasis were 49.2%, 68.6%, and 47.6%, respectively. When inguinal LN metastases were treated as N3, the 5-year OS rates were 66.7% for those with T1N3 and T2N3 disease, and 49.2% for those with T3N3 disease. The inguinal LN of ACA was evaluated and staged as the intermediate LN to devise an appropriate treatment strategy.

Integrative Multiomics Analyses Identify Molecular Subtypes of Head and Neck Squamous Cell Carcinoma with Distinct Therapeutic Vulnerabilities.

Substantial heterogeneity in molecular features, patient prognoses, and therapeutic responses in head and neck squamous cell carcinomas (HNSCC) highlights the urgent need to develop molecular classifications that reliably and accurately reflect tumor behavior and inform personalized therapy. Here, we leveraged the similarity network fusion bioinformatics approach to jointly analyze multiomics datasets spanning copy number variations, somatic mutations, DNA methylation, and transcriptomic profiling and derived a prognostic classification system for HNSCC. The integrative model consistently identified three subgroups (IMC1-3) with specific genomic features, biological characteristics, and clinical outcomes across multiple independent cohorts. The IMC1 subgroup included proliferative, immune-activated tumors and exhibited a more favorable prognosis. The IMC2 subtype harbored activated EGFR signaling and an inflamed tumor microenvironment with cancer-associated fibroblast/vascular infiltrations. Alternatively, the IMC3 group featured highly aberrant metabolic activities and impaired immune infiltration and recruiting. Pharmacogenomics analyses from in silico predictions and from patient-derived xenograft model data unveiled subtype-specific therapeutic vulnerabilities including sensitivity to cisplatin and immunotherapy in IMC1 and EGFR inhibitors (EGFRi) in IMC2, which was experimentally validated in patient-derived organoid models. Two signatures for prognosis and EGFRi sensitivity were developed via machine learning. Together, this integrative multiomics clustering for HNSCC improves current understanding of tumor heterogeneity and facilitates patient stratification and therapeutic development tailored to molecular vulnerabilities. Significance: Head and neck squamous cell carcinoma classification using integrative multiomics analyses reveals subtypes with distinct genetics, biological features, clinicopathological traits, and therapeutic vulnerabilities, providing insights into tumor heterogeneity and personalized treatment strategies.

Chronic myelomonocytic leukemia with ring sideroblasts/SF3B1 mutation presents with low monocyte count and resembles myelodysplastic syndromes with-RS/SF3B1 mutation in terms of phenotype and prognosis.

Chronic myelomonocytic leukemia (CMML) and myelodysplastic syndromes (MDS) with ring sideroblasts (RS) or SF3B1 mutation (MDS-RS/SF3B1) differ in many clinical features, but share others, such as anemia. RS and SF3B1 mutation can also be found in CMML. We compared CMML with and without RS/SF3B1 and MDS-RS/SF3B1 considering the criteria established by the 2022 World Health Organization classification. A total of 815 patients were included (CMML, n=319, CMML-RS/SF3B1, n=172 and MDS-RS/SF3B1, n=324). The percentage of RS was ≥15% in almost all CMML-RS/SF3B1 patients (169, 98.3%) and most (125, 72.7%) showed peripheral blood monocyte counts between 0.5 and 0.9 x109/L and low risk prognostic categories. CMML-RS/SF3B1 differed significantly from classical CMML in the main clinical characteristics, whereas it resembled MDS-RS/SF3B1. At a molecular level, CMML and CMML-RS/SF3B1 had a significantly higher frequency of mutations in TET2 (mostly multi-hit) and ASXL1 (p=0.013) and CMML had a significantly lower frequency of DNMT3A and SF3B1 mutations compared to CMML/MDS-RS/SF3B1. Differences in the median overall survival among the three groups were statistically significant: 6.75 years (95% confidence interval [CI] 5.41-8.09) for CMML-RS/SF3B1 vs. 3.17 years (95% CI 2.56-3.79) for CMML vs. 16.47 years (NA) for MDS-RS/SF3B1, p<0.001. Regarding patients with CMML and MDS, both with SF3B1 mutation, survival did not significantly differ. CMML had a higher risk of transformation to acute myeloid leukemia (24% at 8 years, 95%CI 19%-30%). CMML-RS/SF3B1 mutation resembles MDS-RS/SF3B1 in terms of phenotype and clearly differs from CMML. The presence of ≥15% RS and/or SF3B1 in CMML is associated with a low monocyte count. SF3B1 mutation clearly improves the prognosis of CMML.

Development of the UroARC Surgical Calculator: A Novel Risk Calculator for Older Adults Undergoing Surgery for Bladder Outlet Obstruction.

Bladder outlet obstruction (BOO) is common in older adults. Many older adults who pursue surgery have additional vulnerabilities affecting surgical risk, including frailty. A clinical tool that builds on frailty to predict surgical outcomes for the spectrum of BOO procedures would be helpful to aid in surgical decision-making but does not currently exist. Medicare beneficiaries undergoing BOO surgery from 2014 to 2016 were identified and analyzed using the Medicare MedPAR, Outpatient, and Carrier files. Eight different BOO surgery categories were created. Baseline frailty was calculated for each beneficiary using the Claims-Based Frailty Index (CFI). All 93 variables in the CFI and the 17 variables in the Charlson Comorbidity Index were individually entered into stepwise logistic regression models to determine variables most highly predictive of complications. Similar and duplicative variables were combined into categories. Calibration curves and tests of model fit, including C statistics, Brier scores, and Spiegelhalter P values, were calculated to ensure the prognostic accuracy for postoperative complications. In total, 212,543 beneficiaries were identified. Approximately 42.5% were prefrail (0.15 ≤ CFI < 0.25), 8.7% were mildly frail (0.25 ≤ CFI < 0.35), and 1.2% were moderately-to-severely frail (CFI ≥0.35). Using stepwise logistic regression, 13 distinct prognostic variable categories were identified as the most reliable predictors of postoperative outcomes. Most models demonstrated excellent model discrimination and calibration with high C statistic and Spiegelhalter P values, respectively, and high accuracy with low Brier scores. Calibration curves for each outcome demonstrated excellent model fit. This novel risk assessment tool may help guide surgical prognostication among this vulnerable population.

Expansion of the National Amyloidosis Centre staging system to detect early mortality in transthyretin cardiac amyloidosis.

Transthyretin cardiac amyloidosis (ATTR-CA) is stratified into prognostic categories using the National Amyloidosis Centre (NAC) staging system. The aims of this study were to further expand the existing NAC staging system to incorporate an additional disease stage that would identify patients at high risk of early mortality. The traditional NAC staging system (stage 1: N-terminal pro-B-type natriuretic peptide [NT-proBNP] ≤3000 ng/L and estimated glomerular filtration rate [eGFR] ≥45 ml/min; stage 3: NT-proBNP >3000 ng/L and eGFR <45 ml/min; stage 2: remainder) was expanded by the introduction of a new stage 4 (defined as NT-proBNP ≥10 000 ng/L irrespective of eGFR) and studied in 2042 patients. The optimal NT-proBNP cut-point was established using time-dependent receiver operating characteristic curves in the subgroup of patients with NAC stage 3 disease. Mortality at 1 year according to NAC stage was 2.3% (n = 20/886) for stage 1, 8.8% (n = 62/706) for stage 2, 10.4% (n = 28/270) for stage 3, and 30.6% (n = 55/180) for stage 4 (log-rank p < 0.001). After adjustment for age, mortality hazard for stage 4 was >15-fold higher than that of stage 1 (hazard ratio [HR] 15.5; 95% confidence interval [CI] 9.3-26.1) and >3-fold higher than that of stage 3 (HR 3.4; 95% CI 2.2-5.4). The increased risk of early mortality was consistent across the different genotypes and subclasses of patients based on the severity of heart failure symptoms and echocardiographic parameters. The proposed modification of the NAC staging system identifies patients with ATTR-CA at a high risk of early mortality, who may benefit from a more intensive treatment strategy, and who are most likely to experience an event early in the course of a clinical trial.

Are micro-RNA 21 and 143 indicative as prognostic biomarkers in dedifferentiated endometrial adenocarcinoma?

Dedifferentiated endometrial adenocarcinoma (DEAC) is a rare, aggressive subtype, accounting for 2% of all endometrial cancers. Poor survival in DEAC prompts the need for effective treatment modalities through better prognostic classification. MicroRNAs (miRNA) have essential roles in tumor angiogenesis, which might enable their use as novel biomarkers. In this study, we aimed to reveal the relationship between the expression of miRNA-21 and miRNA-143, which are associated with angiogenesis, and the prognosis of DEAC. The study included six cases diagnosed with DEAC. The expression levels of miRNA-21 and miRNA-143 were detected by quantitative real-time PCR. Microvascular density (MVD) was measured by CD34 staining. All data and effects on survival were compared for statistical significance. Six cases diagnosed with DEAC were included in the study. The percentage of undifferentiated components ranged from 50 to 90%. The second component of differentiated carcinoma was detected as endometrioid (3/5 grade I, 1/5 grade II, 1/5 grade III) in five cases and serous in one case. The mean MVD was 27 (range 17-44, SD 9.4).In three cases, miRNA-21 expression was down-regulated in neoplastic areas compared to non-neoplastic areas. On the contrary, it was found to be up-regulated in the remaining three cases. MiRNA-143 expression decreased in four cases and increased in two cases. Based on these findings, we found a significant irregular expression of miRNA-21 in DEACs. As in other cancers, angiogenesis is significantly associated with survival in DEACs. This study provides initial data for revealing possible implications of miRNAs as prognostic indicators in DEAC.

Biomarkers in breast cancer 2024: an updated consensus statement by the Spanish Society of Medical Oncology and the Spanish Society of Pathology.

This revised consensus statement of the Spanish Society of Medical Oncology (SEOM) and the Spanish Society of Pathological Anatomy (SEAP) updates the recommendations for biomarkers use in the diagnosis and treatment of breast cancer that we first published in 2018. The expert group recommends determining in early breast cancer the estrogen receptor (ER), progesterone receptor (PR), Ki-67, and Human Epidermal growth factor Receptor 2 (HER2), as well as BReast CAncer (BRCA) genes in high-risk HER2-negative breast cancer, to assist prognosis and help in indicating the therapeutic options, including hormone therapy, chemotherapy, anti-HER2 therapy, and other targeted therapies. One of the four available genetic prognostic platforms (Oncotype DX®, MammaPrint®, Prosigna®, or EndoPredict®) may be used in ER-positive patients with early breast cancer to establish a prognostic category and help decide with the patient whether adjuvant treatment may be limited to hormonal therapy. In second-line advanced breast cancer, in addition, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) and estrogen receptor 1 (ESR1) should be tested in hormone-sensitive cases, BRCA gene mutations in HER2-negative cancers, and in triple-negative breast cancer (TNBC), programmed cell death-1 ligand (PD-L1). Newer biomarkers and technologies, including tumor-infiltrating lymphocytes (TILs), homologous recombination deficiency (HRD) testing, serine/threonine kinase (AKT) pathway activation, and next-generation sequencing (NGS), are at this point investigational.

NGS-based stratification refines the risk stratification in T-ALL and identifies a very-high-risk subgroup of patients

AbstractWe previously reported a better outcome in adult and pediatric T-cell acute lymphoblastic leukemia (T-ALL) harboring NOTCH1 and/or FBXW7 mutations without alterations of K-N-RAS and PTEN genes. Availability of high-throughput next-generation sequencing (NGS) strategies led us to refine the outcome prediction in T-ALL. Targeted whole-exome sequencing of 72 T-ALL–related oncogenes was performed in 198 adults with T-ALLs in first remission from the GRAALL-2003/2005 protocols and 242 pediatric patients with T-ALLs from the FRALLE2000T. This approach enabled the identification of, to our knowledge, the first NGS-based classifier in T-ALL, categorizing low-risk patients as those with N/F, PHF6, or EP300 mutations, excluding N-K-RAS, PI3K pathway (PTEN, PIK3CA, and PIK3R1), TP53, DNMT3A, IDH1/2, and IKZF1 alterations, with a 5-year cumulative incidence of relapse (CIR) estimated at 21%. Conversely, the remaining patients were classified as high risk, exhibiting a 5-year CIR estimated at 47%. We externally validated this stratification in the pediatric cohort. NGS-based classifier was highly prognostic independently of minimal residual disease (MRD) and white blood cell (WBC) counts, in both adult and pediatric cohorts. Integration of the NGS-based classifier into a comprehensive risk-stratification model, including WBC count at diagnosis and MRD at the end of induction, enabled the identification of an adverse-risk subgroup (25%) with a 5-year CIR estimated at 51%, and a favorable-risk group (32%) with a 5-year CIR estimated at 12%. NGS-based stratification combined with WBC and MRD sharpens the prognostic classification in T-ALL and identifies a new subgroup of patients who may benefit from innovative therapeutic approaches. The GRAALL-2003/2005 studies were registered at www.ClinicalTrials.gov as #NCT00222027 and #NCT00327678.

The Glasgow Microenvironment Score: an exemplar of contemporary biomarker evolution in colorectal cancer.

Colorectal cancer remains a leading cause of mortality worldwide. Significant variation in response to treatment and survival is evident among patients with similar stage disease. Molecular profiling has highlighted the heterogeneity of colorectal cancer but has had limited impact in daily clinical practice. Biomarkers with robust prognostic and therapeutic relevance are urgently required. Ideally, biomarkers would be derived from H&E sections used for routine pathological staging, have reliable sensitivity and specificity, and require minimal additional training. The biomarker targets would capture key pathological features with proven additive prognostic and clinical utility, such as the local inflammatory response and tumour microenvironment. The Glasgow Microenvironment Score (GMS), first described in 2014, combines assessment of peritumoural inflammation at the invasive margin with quantification of tumour stromal content. Using H&E sections, the Klintrup-Mäkinen (KM) grade is determined by qualitative morphological assessment of the peritumoural lymphocytic infiltrate at the invasive margin and tumour stroma percentage (TSP) calculated in a semi-quantitative manner as a percentage of stroma within the visible field. The resulting three prognostic categories have direct clinical relevance: GMS 0 denotes a tumour with a dense inflammatory infiltrate/high KM grade at the invasive margin and improved survival; GMS 1 represents weak inflammatory response and low TSP associated with intermediate survival; and GMS 2 tumours are typified by a weak inflammatory response, high TSP, and inferior survival. The prognostic capacity of the GMS has been widely validated while its potential to guide chemotherapy has been demonstrated in a large phase 3 trial cohort. Here, we detail its journey from conception through validation to clinical translation and outline the future for this promising and practical biomarker.

A Comprehensive Review and Insights into the New Entity of Differentiated High-Grade Thyroid Carcinoma.

Differentiated high-grade thyroid carcinoma (DHGTC) is a new subset within the spectrum of thyroid malignancies. This review aims to provide a comprehensive overview of DHGTC, focusing on its historical perspective, diagnosis, clinical characteristics, molecular profiles, management, and prognosis. DHGTC demonstrates an intermediate prognosis that falls between well-differentiated thyroid carcinoma and anaplastic thyroid carcinoma. Previously unenumerated, this entity is now recognized for its significant impact. Patients with DHGTC often present at an older age with advanced disease and exhibit aggressive clinical behavior. Molecularly, DHGTC shares similarities with other thyroid malignancies, harboring driver mutations such as BRAFV600E and RAS, along with additional late mutations. The unique behavior and histologic features of DHGTC underscore the necessity of precise classification for prognostication and treatment selection. This highlights the critical importance of accurate diagnosis and recognition by pathologists to enrich future research on this entity further.