Prognostic Value For Overall Survival Research Articles

TIGIT expression on neoplastic cells is a poor prognostic factor for adult T-cell leukaemia/lymphoma

Adult T-cell leukaemia/lymphoma (ATLL) is an aggressive peripheral T-cell neoplasm with a poor prognosis. T-cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domains (TIGIT) is an immune checkpoint receptor expressed on T and natural killer cells. Although increased TIGIT expression in the tumour microenvironment is associated with poor prognosis in various neoplasms, its relevance in ATLL remains unknown. Herein, we investigated the clinicopathological impact of TIGIT expression on ATLL using immunohistochemistry. TIGIT expression was detected in 21 of 84 patients (25%). A partial association between the clinical features and immune checkpoint molecules and the expression of TIGIT was found including sIL-2R, CD86 and GITR. TIGIT-positive patients [median survival time (MST) 8.9 months, 95% confidence interval (CI) 7.7-15.6] had inferior overall survival compared with TIGIT-negative patients (MST 18.7 months, 95% CI 12.0-36.4) (p=0.0124]. TIGIT expression maintained its prognostic value for overall survival in both univariate and multivariate analyses [hazard ratio (HR) 1.909; 95% CI 1.044-3.488; p=0.0356]. Further studies are required to clarify the clinical and biological significance of TIGIT expression in patients with ATLL.

Mapping the genetic landscape establishing a tumor immune microenvironment favorable for anti-PD-1 response in mice and humans.

Identifying host genetic factors modulating immune checkpoint inhibitor (ICI) efficacy has been experimentally challenging because of variations in both host and tumor genomes, differences in the microbiome, and patient life exposures. Utilizing the Collaborative Cross (CC) multi-parent mouse genetic resource population, we developed an approach that fixes the tumor genomic configuration while varying host genetics. With this approach, we discovered that response to anti-PD-1 (aPD1) immunotherapy was significantly heritable in four distinct murine tumor models (H2 between 0.18-0.40). For the MC38 colorectal carcinoma system (H2 = 0.40), we mapped four significant ICI response quantitative trait loci (QTL) localized to mouse chromosomes (mChr) 5, 9, 15 and 17, and identified significant epistatic interactions between specific QTL pairs. Differentially expressed genes within these QTL were highly enriched for immune genes and pathways mediating allograft rejection and graft vs host disease. Using a cross species analytical approach, we found a core network of 48 genes within the four QTLs that showed significant prognostic value for overall survival in aPD1 treated human cohorts that outperformed all other existing validated immunotherapy biomarkers, especially in human tumors of the previously defined immune subtype 4. Functional blockade of two top candidate immune targets within the 48 gene network, GM-CSF and high affinity IL-2/IL-15 signaling, completely abrogated the MC38 tumor transcriptional response to aPD1 therapy in vivo. Thus, we have established a powerful cross species in vivo platform capable of uncovering host genetic factors that establish the tumor immune microenvironment configuration propitious for ICI response.

Gastro-Esophageal Cancer: Can Radiomic Parameters from Baseline 18F-FDG-PET/CT Predict the Development of Distant Metastatic Disease?

We aimed to determine if clinical parameters and radiomics combined with sarcopenia status derived from baseline 18F-FDG-PET/CT could predict developing metastatic disease and overall survival (OS) in gastroesophageal cancer (GEC). Patients referred for primary staging who underwent 18F-FDG-PET/CT from 2008 to 2019 were evaluated retrospectively. Overall, 243 GEC patients (mean age = 64) were enrolled. Clinical, histopathology, and sarcopenia data were obtained, and primary tumor radiomics features were extracted. For classification (early-stage vs. advanced disease), the association of the studied parameters was evaluated. Various clinical and radiomics models were developed and assessed. Accuracy and area under the curve (AUC) were calculated. For OS prediction, univariable and multivariable Cox analyses were performed. The best model included PET/CT radiomics features, clinical data, and sarcopenia score (accuracy = 80%; AUC = 88%). For OS prediction, various clinical, CT, and PET features entered the multivariable analysis. Three clinical factors (advanced disease, age ≥ 70 and ECOG ≥ 2), along with one CT-derived and one PET-derived radiomics feature, retained their significance. Overall, 18F-FDG PET/CT radiomics seems to have a potential added value in identifying GEC patients with advanced disease and may enhance the performance of baseline clinical parameters. These features may also have a prognostic value for OS, improving the decision-making for GEC patients.

The Prognostic Significance of Tumor SUVmax Value in Pre- and Post-Chemoradiotherapy 18F-FDG PET/CT Imaging in Patients with Localized and Advanced Head and Neck Squamous Cell Carcinoma

Background: Some parameters of 18F-2-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) can predict tumor chemosensitivity and survival in patients with head and neck squamous cell carcinoma (HNSCC). Aim: The aim of the study was to investigate the prognostic value of pre- and post-treatment maximum standardized uptake values (SUVmax) in 18F-FDG PET/CT imaging for predicting mortality in patients with HNSCC, as well as its prognostic value in terms of disease progression, overall survival (OS), and progression-free survival (PFS). Methods: This retrospective study included 37 patients with a histopathological diagnosis of HNSCCs between 2015 and 2018. In patients with HNSCC, the first 18F-FDG PET/CT imaging was performed for pre-treatment staging, and the second imaging was performed to evaluate post-treatment response. In these imaging studies, SUVmax values of the primary tumor before and after treatment were determined. After the second imaging, patients were re-evaluated and followed up. ROC analysis was used to determine the predictive value of 18F-FDG PET/CT SUVmax parameters in terms of death and progression, and Cox regression analysis was used to investigate the prognostic value in terms of OS and PFS. Results: Cut-off value 15 for SUVmax1 (pre-treatment) had a significant predictive value for mortality (P = 0.02). Cut-off value 3.1 for SUVmax2 (post-treatment) had a significant predictive value for progression (P = 0.024). In univariate analysis, both SUVmax1 and SUVmax2 values were significant prognostic factors for OS (P = 0.047, P = 0.004). However, for PFS, only the SUVmax2 value was a significant prognostic factor (P = 0.001). Conclusion: SUVmax1 value of the primary tumor at diagnosis in HNSCC patients has a predictive value for mortality and a prognostic value for OS. However, the SUVmax2 value in the primary tumor after treatment is a predictive factor for progression and a prognostic factor for both OS and PFS.

Prognostic value of combining clinical factors, 18F-FDG PET-based intensity, volumetric features, and deep learning predictor in patients with EGFR-mutated lung adenocarcinoma undergoing targeted therapies: a cross-scanner and temporal validation study.

To investigate the prognostic value of 18F-FDG PET-based intensity, volumetric features, and deep learning (DL) across different generations of PET scanners in patients with epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma receiving tyrosine kinase inhibitor (TKI) treatment. We retrospectively analyzed the pre-treatment 18F-FDG PET of 217 patients with advanced-stage lung adenocarcinoma and actionable EGFR mutations who received TKI as first-line treatment. Patients were separated into analog (n = 166) and digital (n = 51) PET cohorts. 18F-FDG PET-derived intensity, volumetric features, ResNet-50 DL of the primary tumor, and clinical variables were used to predict progression-free survival (PFS). Independent prognosticators were used to develop prediction model. Model was developed and validated in the analog and digital PET cohorts, respectively. In the analog PET cohort, female sex, stage IVB status, exon 19 deletion, SUVmax, metabolic tumor volume, and positive DL prediction independently predicted PFS. The model devised from these six prognosticators significantly predicted PFS in the analog (HR = 1.319, p < 0.001) and digital PET cohorts (HR = 1.284, p = 0.001). Our model provided incremental prognostic value to staging status (c-indices = 0.738 vs. 0.558 and 0.662 vs. 0.598 in the analog and digital PET cohorts, respectively). Our model also demonstrated a significant prognostic value for overall survival (HR = 1.198, p < 0.001, c-index = 0.708 and HR = 1.256, p = 0.021, c-index = 0.664 in the analog and digital PET cohorts, respectively). Combining 18F-FDG PET-based intensity, volumetric features, and DL with clinical variables may improve the survival stratification in patients with advanced EGFR-mutated lung adenocarcinoma receiving TKI treatment. Implementing the prediction model across different generations of PET scanners may be feasible and facilitate tailored therapeutic strategies for these patients.

Comparison of discovery rates and prognostic utility of [68Ga]Ga-PSMA-11 PET/CT and circulating tumor DNA in prostate cancer—a cross-sectional study

BackgroundCirculating-tumor DNA (ctDNA) and prostate-specific membrane antigen (PSMA) ligand positron-emission tomography (PET) enable minimal-invasive prostate cancer (PCa) detection and survival prognostication. The present study aims to compare their tumor discovery abilities and prognostic values.MethodsOne hundred thirty men with confirmed PCa (70.5 ± 8.0 years) who underwent [68Ga]Ga-PSMA-11 PET/CT (184.8 ± 19.7 MBq) imaging and plasma sample collection (March 2019–August 2021) were included. Plasma-extracted cell-free DNA was subjected to whole-genome-based ctDNA analysis. PSMA-positive tumor lesions were delineated and their quantitative parameters extracted. ctDNA and PSMA PET/CT discovery rates were compared, and the prognostic value for overall survival (OS) was evaluated.ResultsPSMA PET discovery rates according to castration status and PSA ranges did differ significantly (P = 0.013, P < 0.001), while ctDNA discovery rates did not (P = 0.311, P = 0.123). ctDNA discovery rates differed between localized and metastatic disease (P = 0.013). Correlations between ctDNA concentrations and PSMA-positive tumor volume (PSMA-TV) were significant in all (r = 0.42, P < 0.001) and castration-resistant (r = 0.65, P < 0.001), however not in hormone-sensitive patients (r = 0.15, P = 0.249). PSMA-TV and ctDNA levels were associated with survival outcomes in the Logrank (P < 0.0001, P < 0.0001) and multivariate Cox regression analysis (P = 0.0023, P < 0.0001).ConclusionThese findings suggest that PSMA PET imaging outperforms ctDNA analysis in detecting prostate cancer across the whole spectrum of disease, while both modalities are independently highly prognostic for survival outcomes.Graphical

CD200 is overexpressed in the pancreatic tumor microenvironment and predictive of overall survival

Pancreatic cancer is an aggressive disease with a 5 year survival rate of 13%. This poor survival is attributed, in part, to limited and ineffective treatments for patients with metastatic disease, highlighting a need to identify molecular drivers of pancreatic cancer to target for more effective treatment. CD200 is a glycoprotein that interacts with the receptor CD200R and elicits an immunosuppressive response. Overexpression of CD200 has been associated with differential outcomes, depending on the tumor type. In the context of pancreatic cancer, we have previously reported that CD200 is expressed in the pancreatic tumor microenvironment (TME), and that targeting CD200 in murine tumor models reduces tumor burden. We hypothesized that CD200 is overexpressed on tumor and stromal populations in the pancreatic TME and that circulating levels of soluble CD200 (sCD200) have prognostic value for overall survival. We discovered that CD200 was overexpressed on immune, stromal, and tumor populations in the pancreatic TME. Particularly, single-cell RNA-sequencing indicated that CD200 was upregulated on inflammatory cancer-associated fibroblasts. Cytometry by time of flight analysis of PBMCs indicated that CD200 was overexpressed on innate immune populations, including monocytes, dendritic cells, and monocytic myeloid-derived suppressor cells. High sCD200 levels in plasma correlated with significantly worse overall and progression-free survival. Additionally, sCD200 correlated with the ratio of circulating matrix metalloproteinase (MMP) 3: tissue inhibitor of metalloproteinase (TIMP) 3 and MMP11/TIMP3. This study highlights the importance of CD200 expression in pancreatic cancer and provides the rationale for designing novel therapeutic strategies that target this protein.

A three-gene expression score for predicting clinical benefit to anti-PD-1 blockade in advanced renal cell carcinoma.

In the advanced renal cell carcinoma (RCC) scenario, there are no consistent biomarkers to predict the clinical benefit patients derived from immune checkpoint blockade (ICB). Taking this into consideration, herein, we conducted a retrospective study in order to develop and validate a gene expression score for predicting clinical benefit to the anti-PD-1 antibody nivolumab in the context of patients diagnosed with advanced clear cell RCC enrolled in the CheckMate-009, CheckMate-010, and CheckMate-025 clinical trials. First, a three-gene expression score (3GES) with prognostic value for overall survival integrating HMGA1, NUP62, and ARHGAP42 transcripts was developed in a cohort of patients treated with nivolumab. Its prognostic value was then validated in the TCGA-KIRC cohort. Second, the predictive value for nivolumab was confirmed in a set of patients from the CheckMate-025 phase 3 clinical trial. Lastly, we explored the correlation of our 3GES with different clinical, molecular, and immune tumor characteristics. If the results of this study are definitively validated in other retrospective and large-scale, prospective studies, the 3GES will represent a valuable tool for guiding the design of ICB-based clinical trials in the aRCC scenario in the near future.

Prognostic Value of S100 Family mRNA Expression in Hepatocellular Carcinoma.

The S100 family contains more than 20 Ca2+-binding proteins that participate in numerous cellular biological processes. However, the prognostic value of individual S100s in hepatocellular carcinoma (HCC) remains unclear. Therefore, we comprehensively assessed the prognostic value of S100s in HCC. The mRNA level of S100s in distinct types of cancer was analyzed through Oncomine. The clinical prognostic significance of each S100 was evaluated using Kaplan-Meier plotter and OncoLnc. The expression and mutation of S100s were determined through cBioPortal. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were used to predict the functions and pathways of S100s. The analyses revealed that, relative to normal tissues, liver cancer tissues showed aberrant mRNA expression of most S100s. In the survival analysis with Kaplan-Meier plotter, elevated expression levels of S100PBP, S100A2, S100A7, S100A10, and S100A13 were related to shorter overall survival (OS), whereas increased S100A5 expression was associated with longer OS. Moreover, results obtained using OncoLnc showed that increased expression levels of S100P, S100PBP, S100A13, S100A11, S100A10, and S100A2 were related to shorter OS. Thus, S100PBP, S100A13, S100A10, and S100A2 exhibited the same prognostic trend in the 2 databases. However, all S100 member gene mutational changes had no considerable prognostic value in OS and disease-free survival of HCC patients. Although the findings need to be further confirmed by experiments, they provide new evidence for the prognostic significance of the S100s in HCC.

Identification of prognostic factors for survival in patients with metastatic gastric adenocarcinoma in a Mexican population

Introduction and aimsGastric adenocarcinoma is among the high-ranking tumors, with respect to frequency and mortality, worldwide. The inflammatory process and immune system activity are associated with oncologic control. Our aim was to identify whether the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and other variables are prognostic factors for survival in patients with metastatic gastric cancer in a Mexican population. Material and methodsPatients diagnosed with metastatic gastric adenocarcinoma, hospitalized within the time frame of December 2011 to 2021, were analyzed. The NLR, PLR, and albumin and hemoglobin levels obtained from blood samples were calculated. Functional status (ECOG and Karnofsky), sex, histology, and the presence of signet ring cells were also considered possible prognostic factors. Each factor’s prognostic value for overall survival was determined through univariate and multivariate analyses. ResultsThe study included 956 patients diagnosed with metastatic gastric cancer, of whom 494 (51.7%) were men and 462 (48.3%) were women. The main histologic finding was diffuse adenocarcinoma (n = 619, 64.7%), followed by intestinal adenocarcinoma (n = 293, 30.6%), and the presence of signet ring cells was found in 659 (68.9%) patients. Diagnostic laparoscopy was performed on 238 patients (24.9%) to confirm peritoneal carcinomatosis. The multivariate analysis showed that an NLR above 3.2 (HR 1.51, 95% CI 1.27–1.8; p < 0.001), albumin below 3.5 g/dl (HR 1.25, CI 1.06–1.47; p = 0.006), and an ECOG performance status of 2 or higher (HR 1.39, CI 1.10–1.76; p = 0.005) were independent factors that predicted a lower survival rate, whereas a Karnofsky score above 70% (HR 0.69, CI 0.53–0.91; p = 0.008) was associated with a better survival rate. Lastly, the PLR was not statistically significant in the multivariate analysis. ConclusionsThe NLR, nutritional status assessed through albumin measurement, and functional status can act as independent prognostic survival factors in hospitalized Mexican patients diagnosed with metastatic gastric adenocarcinoma and be taken into account during therapeutic decision-making.

Subtype-Specific Survival of Young Women with Breast Cancer and Its Interaction with the Germline BRCA Status.

Data are scarce on the role of pathogenic germline variants in BRCA1 and BRCA2 (gBRCAm) in subtype-specific survival in young women who develop breast cancer under the age of 40. This retrospective, real-world cohort study assessed the distant disease-free survival (DDFS) and overall survival (OS) of young women diagnosed with breast cancer between 2008 and 2019 while taking into consideration the interaction of clinical subtypes and the gBRCA status. Among 473 women, HR+/Her2- was the most common subtype (49.0%), followed by TNBC (31.3%), HR+/Her2+ (13.7%), and Her2+/HR- (5.9%). The gBRCA status was known for 319 cases (gBRCAwt (wild-type - without pathogenic variants in BRCA1 or BRCA2): 204, gBRCA1m: 83, gBRCA2m: 31, 1 patient with both). The distribution of clinical subtypes varied depending on the gBRCA status (p < 0.001). In survival analysis with a median follow-up of 43 months, the unadjusted DDFS and OS were worse for gBRCAwt TNBC compared to both HR+ subtypes, but not for gBRCAm TNBC patients. T-stage, nodal involvement, and the gBRCA status were identified as significant for survival in TNBC. In TNBC, gBRCAm was associated with better DDFS and OS than gBRCAwt (5-year DDFS 81.4% vs. 54.3%, p = 0.012 and 5-year OS 96.7% vs. 62.7%, p < 0.001). In contrast, in HR+/Her2- patients, gBRCAm patients showed a tendency for worse survival, though not statistically significant. Subtype-specific survival in young women with breast cancer needs to be evaluated in interaction with the gBRCA status. For TNBC, gBRCAm is of favorable prognostic value for overall survival, while patients with gBRCAwt TNBC need to be considered to have the highest risk for adverse survival outcomes.

Impact of presentation timing in metastatic hormone-sensitive prostate cancer: Characterization of patients and identification of prognostic factors.

The treatment and surveillance of metastatic hormone-sensitive prostate cancer (mHSPC) has evolved since the introduction of several treatment intensification options associated with hormonal blockade and classifications based on the timing of metastatic disease presentation and disease volume. Using a hospital-based registry, we aimed to assess whether these new classifications are applicable to our population, as few studies have demonstrated their prognostic value for overall survival (OS) and time to development of castration-resistant prostate cancer (CRPC), and to establish prognostic factors in our population. A retrospective cohort of mHSPC patients who were attended at an oncology referral hospital in Bogota between 2017 and 2021 were included in this study. The primary and secondary endpoints were OS and time to CRPC. The distribution of outcome measures was estimated using the Kaplan-Meier method. Proportional hazard models were constructed using the Cox regression approach and stratified according to risk factors. The study cohort included 373 patients. The median castration resistance-free survival was 48 months (CI: 32-73 months), and OS was 43 months (CI: 37-48 months). In multivariate analysis, nodal staging, ECOG status, and surgical castration were independent prognostic factors. In our hospital-based registry, the independent impact of the time of presentation on castration-resistant-free survival or OS could not be demonstrated, nor could the grouping of prognostic categories based on metastatic presentation temporality and volume. Other independent prognostic factors have been proposed.

MIHIC: a multiplex IHC histopathological image classification dataset for lung cancer immune microenvironment quantification.

Immunohistochemistry (IHC) is a widely used laboratory technique for cancer diagnosis, which selectively binds specific antibodies to target proteins in tissue samples and then makes the bound proteins visible through chemical staining. Deep learning approaches have the potential to be employed in quantifying tumor immune micro-environment (TIME) in digitized IHC histological slides. However, it lacks of publicly available IHC datasets explicitly collected for the in-depth TIME analysis. In this paper, a notable Multiplex IHC Histopathological Image Classification (MIHIC) dataset is created based on manual annotations by pathologists, which is publicly available for exploring deep learning models to quantify variables associated with the TIME in lung cancer. The MIHIC dataset comprises of totally 309,698 multiplex IHC stained histological image patches, encompassing seven distinct tissue types: Alveoli, Immune cells, Necrosis, Stroma, Tumor, Other and Background. By using the MIHIC dataset, we conduct a series of experiments that utilize both convolutional neural networks (CNNs) and transformer models to benchmark IHC stained histological image classifications. We finally quantify lung cancer immune microenvironment variables by using the top-performing model on tissue microarray (TMA) cores, which are subsequently used to predict patients' survival outcomes. Experiments show that transformer models tend to provide slightly better performances than CNN models in histological image classifications, although both types of models provide the highest accuracy of 0.811 on the testing dataset in MIHIC. The automatically quantified TIME variables, which reflect proportions of immune cells over stroma and tumor over tissue core, show prognostic value for overall survival of lung cancer patients. To the best of our knowledge, MIHIC is the first publicly available lung cancer IHC histopathological dataset that includes images with 12 different IHC stains, meticulously annotated by multiple pathologists across 7 distinct categories. This dataset holds significant potential for researchers to explore novel techniques for quantifying the TIME and advancing our understanding of the interactions between the immune system and tumors.

Comprehensive analysis the prognostic and immune characteristics of mitochondrial transport-related gene SFXN1 in lung adenocarcinoma

BackgroundMitochondria, which serve as the fundamental organelle for cellular energy and metabolism, are closely linked to the growth and survival of cancer cells. This study aims to identify and assess Sideroflexin1 (SFXN1), an unprecedented mitochondrial gene, as a potential prognostic biomarker for lung adenocarcinoma (LUAD).MethodsThe mRNA and protein levels of SFXN1 were investigated based on the Cancer Genome Atlas (TCGA) LUAD dataset, and then validated by real-time quantitative PCR, Western Blotting and immunohistochemistry from our clinical samples. The clinical correlation and prognostic value were evaluated by the TCGA cohort and verified via our clinical dataset (n = 90). The somatic mutation, drug sensitivity data, immune cell infiltration and single-cell RNA sequencing data of SFXN1 were analyzed through public databases.ResultsSFXN1 was markedly upregulated at both mRNA and protein levels in LUAD, and high expression of SFXN1 were correlated with larger tumor size, positive lymph node metastasis, and advanced clinical stage. Furthermore, SFXN1 upregulation was significantly associated with poor clinical prognosis. SFXN1 co-expressed genes were also analyzed, which were mainly involved in the cell cycle, central carbon metabolism, DNA repair, and the HIF-1α signaling pathway. Additionally, SFXN1 expression correlated with the expression of multiple immunomodulators, which act to regulate the tumor immune microenvironment. Results also demonstrated an association between SFXN1 expression and increased immune cell infiltration, such as activated CD8 + T cells, natural killer cells (NKs), activated dendritic cells (DCs), and macrophages. LUAD patients with high SFXN1 expression exhibited heightened sensitivity to multiple chemotherapies and targeted drugs and predicted a poor response to immunotherapy. SFXN1 represented an independent prognostic marker for LUAD patients with an improved prognostic value for overall survival when combined with clinical stage information.ConclusionsSFXN1 is frequently upregulated in LUAD and has a significant impact on the tumor immune environment. Our study uncovers the potential of SFXN1 as a prognostic biomarker and as a novel target for intervention in LUAD.

Human leukocyte antigen evolutionary divergence as a novel risk factor for donor selection in acute lymphoblastic leukemia patients undergoing haploidentical hematopoietic stem cell transplantation.

The human leukocyte antigen (HLA) evolutionary divergence (HED) reflects immunopeptidome diversity and has been shown to predict the response of tumors to immunotherapy. Its impact on allogeneic hematopoietic stem cell transplantation (HSCT) is controversial in different studies. In this study, we retrospectively analyzed the clinical impact of class I and II HED in 225 acute lymphoblastic leukemia patients undergoing HSCT from related haploidentical donors. The HED for recipient, donor, and donor-recipient pair was calculated based on Grantham distance, which accounts for variations in the composition, polarity, and volume of each amino acid within the peptide-binding groove of two HLA alleles. The median value of HED scores was used as a cut-off to stratify patients with high or low HED. The class I HED for recipient (R_HEDclass I) showed the strongest association with cumulative incidence of relapse (12.2 vs. 25.0%, P = 0.00814) but not with acute graft-versus-host disease. The patients with high class II HED for donor-recipient (D/R_HEDclass II) showed a significantly higher cumulative incidence of severe aGVHD than those with low D/R_HEDclass II (24.0% vs. 6.1%, P = 0.0027). Multivariate analysis indicated that a high D/R_HEDclass II was an independent risk factor for the development of severe aGVHD (P = 0.007), and a high R_HEDclass I had a more than two-fold reduced risk of relapse (P = 0.028). However, there was no discernible difference in overall survival (OS) or disease-free survival (DFS) for patients with high or low HED, which was inconsistent with the previous investigation. While the observation are limited by the presented single center retrospective cohort, the results show that HED has poor prognostic value in OS or DFS, as well as the associations with relapse and aGVHD. In haploidentical setting, class II HED for donor-recipient pair (D/R_HEDclass II) is an independent and novel risk factor for finding the best haploidentical donor, which could potentially influence clinical practice if verified in larger cohorts.

Identificación de factores pronósticos para supervivencia en pacientes con adenocarcinoma gástrico metastásico en la población mexicana

Introduction and aimsGastric adenocarcinoma is among the high-ranking tumors, with respect to frequency and mortality, worldwide. The inflammatory process and immune system activity are associated with oncologic control. Our aim was to identify whether the neutrophil-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio (PLR), and other variables are prognostic factors for survival in patients with metastatic gastric cancer in a Mexican population. Material and methodsPatients diagnosed with metastatic gastric adenocarcinoma, hospitalized within the time frame of December 2011 to 2021, were analyzed. The NLR, PLR, and albumin and hemoglobin levels obtained from blood samples were calculated. Functional status (ECOG and Karnofsky), sex, histology, and the presence of signet ring cells were also considered possible prognostic factors. Each factor's prognostic value for overall survival was determined through univariate and multivariate analyses. ResultsThe study included 956 patients diagnosed with metastatic gastric cancer, of whom 494 (51.7%) were men and 462 (48.3%) were women. The main histologic finding was diffuse adenocarcinoma (n=619, 64.7%), followed by intestinal adenocarcinoma (n=293, 30.6%), and the presence of signet ring cells was found in 659 (68.9%) patients. Diagnostic laparoscopy was performed on 238 patients (24.9%) to confirm peritoneal carcinomatosis. The multivariate analysis showed that an NLR above 3.2 (HR 1.51, 95% CI 1.27-1.8; p<0.001), albumin below 3.5g/dl (HR 1.25, 95% CI 1.06-1.47; p=0.006), and an ECOG performance status of 2 or higher (HR 1.39, 95% CI 1.10-1.76; p=0.005) were independent factors that predicted a lower survival rate, whereas a Karnofsky score above 70% (HR 0.69, 95% CI 0.53-0.91; p=0.008) was associated with a better survival rate. Lastly, the PLR was not statistically significant in the multivariate analysis. ConclusionsThe NLR, nutritional status assessed through albumin measurement, and functional status can act as independent prognostic survival factors in hospitalized Mexican patients diagnosed with metastatic gastric adenocarcinoma, and be taken into account during therapeutic decision-making.

Frailty assessment by two screening instruments in non-elderly patients with head and neck cancer

PurposeFrailty assessment is often overlooked in non-elderly patients with cancer, possibly due to the lack of an effective frailty screening tool. This study aimed to evaluate the performance of two modern frailty screening tools, the Flemish version of the Triage Risk Screening Tool (fTRST) and the modified 5-Item Frailty Index (mFI-5), compared to the gold standard comprehensive geriatric assessment (GA) among non-elderly patients with head and neck cancer (HNC). MethodsWe prospectively included 354 consecutive patients aged < 65 years with newly diagnosed HNC scheduled for definitive concurrent chemoradiotherapy (CCRT) at three academic hospitals in Taiwan between January 2020 and December 2022. Frailty assessment using the GA, fTRST, and mFI-5 was performed in all patients to evaluate the relationship between frailty and treatment outcomes. ResultsThe prevalence of frailty was 27.1%, 37.0%, and 42.4% based on GA, mFI-5, and fTRST, respectively. mFI-5 and fTRST demonstrated good predictive value in identifying frail patients compared to the GA. Patients with frailty, as defined by GA, mFI-5, and fTRST, exhibited higher risks of treatment-related complications, incomplete treatment, and poorer baseline quality of life (QoL). However, only GA showed significant prognostic value for overall survival. ConclusionsFrailty assessment using fTRST and mFI-5 is valuable for predicting treatment-related adverse events, treatment tolerance, and QoL in non-elderly patients with HNC. Incorporating frailty assessment into the management of non-elderly cancer patients can aid in the identification of high-risk individuals. However, the performance of these tools varies, highlighting the need for further validation and refinement.

A tumor-infiltrating immune cells-related pseudogenes signature based on machine-learning predicts outcomes and immunotherapy responses in ovarian cancer

Previous researches have provided evidence for the significant involvement of pseudogenes in immune-related functions across different types of cancer. However, the mechanisms by which pseudogenes regulate immunity in ovarian cancer (OV) and their potential impact on clinical outcomes remain unclear. To address this gap in knowledge, our study utilized a novel computational framework to analyze a total of 491 samples from three public datasets. We employed a combination of 10 machine-learning algorithms to construct a signature known as the tumor-infiltrating immune cells-related pseudogenes signature (TIICPS). The TIICPS, consisting of 12 pseudogenes, demonstrated independent prognostic value for overall survival, surpassing conventional clinical traits, 62 published signatures, and TP53 and BRCA mutation status in three cohorts. Patients with low TIICPS exhibited heightened immune-related pathways, intricate genomic alterations, substantial immune infiltration, and greater potential for immunotherapy efficacy. Consequently, TIICPS holds promise as a predictive tool for prognosis and immunotherapy response in ovarian cancer.

Trends in Systemic Inflammatory Reaction (SIR) during Paclitaxel and Carboplatin Chemotherapy in Women Suffering from Epithelial Ovarian Cancer.

Epithelial ovarian cancer (EOC) is the most fatal gynaecological malignancy treated with cytoreductive surgery followed by adjuvant taxane-platinum-based chemotherapy. It has been shown that the pretreatment systemic inflammatory reaction (SIR) in women with OC can be evaluated using the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR) and systemic inflammatory index (SII), depending on the stage of disease, and has prognostic value for overall survival. The aim of this study was to evaluate the changes in NLR, LMR, PLR and SII during chemotherapy. A total of 107 women with EOC (23 with type I and 84 with type II tumours) were included in a retrospective single-centre analysis. The Kologomorov-Smirnoff, Kruskal-Wallis or Friedman analysis of variance tests were used for data analysis, and a p value of 0.05 was considered statistically significant. A significant decrease in NLR, PLR and SII but not LMR was observed during adjuvant treatment. Pretreatment NLR, PLR and SII were dependent on disease stage and tumour grade; however, this association was lost during therapy. Additionally, strong and positive mutual correlations between NLR, LMR, PLR and SII were sustained during the whole course of chemotherapy. During first-line adjuvant chemotherapy in women with EOC, a decrease in SIR is confirmed.

A new prognostic model including immune biomarkers, genomic proliferation tumor markers (AURKA and MYBL2) and clinical-pathological features optimizes prognosis in neoadjuvant breast cancer patients.

Up to 30% of breast cancer (BC) patients treated with neoadjuvant chemotherapy (NCT) will relapse. Our objective was to analyze the predictive capacity of several markers associated with immune response and cell proliferation combined with clinical parameters. This was a single-center, retrospective cohort study of BC patients treated with NCT (2001-2010), in whom pretreatment biomarkers were analyzed: neutrophil-to-lymphocyte ratio (NLR) in peripheral blood, CD3+ tumor-infiltrating lymphocytes (TILs), and gene expression of AURKA, MYBL2 and MKI67 using qRT-PCR. A total of 121 patients were included. Median followup was 12 years. In a univariate analysis, NLR, TILs, AURKA, and MYBL2 showed prognostic value for overall survival. In multivariate analyses, including hormone receptor, HER2 status, and response to NCT, NLR (HR 1.23, 95% CI 1.01-1.75), TILs (HR 0.84, 95% CI 0.73-0.93), AURKA (HR 1.05, 95% CI 1.00-1.11) and MYBL2 (HR 1.19, 95% CI 1.05-1.35) remained as independent predictor variables. Consecutive addition of these biomarkers to a regression model progressively increased its discriminatory capacity for survival. Should independent cohort studies validate these findings, management of early BC patients may well be changed.