New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges.

Despite a standardized diagnostic examination, cancer of unknown primary (CUP) is a rare metastatic malignancy with an unidentified tissue of origin (TOO). Patients diagnosed with CUP are typically treated with empiric chemotherapy, although their prognosis is worse than those with metastatic cancer of a known origin. TOO identification of CUP has been employed in precision medicine, and subsequent site-specific therapy is clinically helpful. For example, molecular profiling, including genomic profiling, gene expression profiling, epigenetics and proteins, has facilitated TOO identification. Moreover, machine learning has improved identification accuracy, and non-invasive methods, such as liquid biopsy and image omics, are gaining momentum. However, the heterogeneity in prediction accuracy, sample requirements and technical fundamentals among the various techniques is noteworthy. Accordingly, we systematically reviewed the development and limitations of novel TOO identification methods, compared their pros and cons and assessed their potential clinical usefulness. Our study may help patients shift from empirical to customized care and improve their prognoses.

Autonomic Responses Associated with Olfactory Preferences of Fragrance Consumers: Skin Conductance, Respiration, and Heart Rate.

Assessing the olfactory preferences of consumers is an important aspect of fragrance product development and marketing. With the advancement of wearable device technologies, physiological signals hold great potential for evaluating olfactory preferences. However, there is currently a lack of relevant studies and specific explanatory procedures for preference assessment methods that are based on physiological signals. In response to this gap, a synchronous data acquisition system was established using the ErgoLAB multi-channel physiology instrument and olfactory experience tester. Thirty-three participants were recruited for the olfactory preference experiments, and three types of autonomic response data (skin conductance, respiration, and heart rate) were collected. The results of both individual and overall analyses indicated that olfactory preferences can lead to changes in skin conductance (SC), respiration (RESP), and heart rate (HR). The trends of change in both RESP and HR showed significant differences (with the HR being more easily distinguishable), while the SC did not exhibit significant differences across different olfactory perception preferences. Additionally, gender differences did not result in significant variations. Therefore, HR is more suitable for evaluating olfactory perception preferences, followed by RESP, while SC shows the least effect. Moreover, a logistic regression model with a high accuracy (84.1%) in predicting olfactory perception preferences was developed using the changes in the RESP and HR features. This study has significant implications for advancing the assessment of consumer olfactory preferences.

Heterogeneity and Adjuvant Therapeutic Approaches in MSI-H/dMMR Resectable Gastric Cancer: Emerging Trends in Immunotherapy.

Gastric cancer (GC) remains one of the world's most common and fatal malignant tumors. With a refined understanding of molecular typing in recent years, microsatellite instability (MSI) has become a major molecular typing approach for gastric cancer. MSI is well recognized for its important role during the immunotherapy of advanced GC. However, its value remains unclear in resectable gastric cancer. The reported incidence of microsatellite instability-high (MSI-H)/deficient mismatch repair (dMMR) in resectable gastric cancer varies widely, with no consensus reached on the value of postoperative adjuvant therapy in patients with MSI-H/dMMR resectable GC. It has been established that MSI-H/dMMR tumor cells can elicit an endogenous immune antitumor response and ubiquitously express immune checkpoint ligands such as PD-1 or PD-L1. On the basis of these considerations, MSI-H/dMMR resectable GCs are responsive to adjuvant immunotherapy, although limited research has hitherto been conducted. In this review, we comprehensively describe the differences in geographic distribution and pathological stages in patients with MSI-H/dMMR with resectable gastric cancer and explore the value of adjuvant chemotherapy and immunotherapy on MSI-H/dMMR to provide a foothold for the individualized treatment of this patient population.

Proteomic profiling of gastric cancer with peritoneal metastasis identifies a protein signature associated with immune microenvironment and patient outcome.

BACKGROUND: Peritoneal metastasis (PM) frequently occurs in patients with gastric cancer (GC) and is a major cause of mortality. Risk stratification for PM can optimize decision making in GC treatment. METHODS: A total of 25 GC patients (13 with synchronous, 6 with metachronous PM and 6 PM-free) were included in this study. Quantitative proteomics by high-depth tandem mass tags labeling and whole-exome sequencing were conducted in primary GC and PM samples. Proteomic signature and prognostic model were established by machine learning algorithms in PM and PM-free GC, then validated in two external cohorts. Tumor-infiltrating immune cells in GC were analyzed by CIBERSORT. RESULTS: Heterogeneity between paired primary and PM samples was observed at both genomic and proteomic levels. Compared to primary GC, proteome of PM samples was enriched in RNA binding and extracellular exosomes. 641 differently expressed proteins (DEPs) between primary GC of PM group and PM-free group were screened, which were enriched in extracellular exosome and cell adhesion pathways. Subsequently, a ten-protein signature was derived based on DEPs by machine learning. This signature was significantly associated with patient prognosis in internal cohort and two external proteomic datasets of diffuse and mixed type GC. Tumor-infiltrating immune cell analysis showed that the signature was associated with immune microenvironment of GC. CONCLUSIONS: We characterized proteomic features that were informative for PM progression of GC. A protein signature associated with immune microenvironment and patient outcome was derived, and it could guide risk stratification and individualized treatment.

Semen as a rich source of diagnostic biomarkers for prostate cancer: latest evidence and implications.

Prostate cancer (PCa) is one of the most common cancers in men and the cause of numerous cancer deaths in the world. Nowadays, based on diagnostic criteria, prostate-specific antigen (PSA) evaluation and rectal examination are used to diagnose prostate-related malignancies. However, due to the different types of PCa, there are several doubts about the diagnostic value of PSA. On the other hand, semen is considered an appropriate source and contains various biomarkers in non-invasive diagnosing several autoimmune disorders and malignancies. Evidence suggests that analysis of semen biomarkers could be helpful in PCa diagnosis. Therefore, due to the invasiveness of most diagnostic methods in PCa, the use of semen as a biologic sample containing various biomarkers can lead to the emergence of novel and non-invasive diagnostic approaches. This review summarized recent studies on the use of various seminal biomarkers for diagnosis, prognosis and prediction of PCa.

Combination of UNMIX, PMF model and Pb-Zn-Cu isotopic compositions for quantitative source apportionment of heavy metals in suburban agricultural soils.

Quantitative identification of heavy metals (HM) sources in soils is key to prevention and control of heavy metal pollution. In this study, UNMIX, PMF (Positive matrix factorization) model and Pb-Zn-Cu isotopic compositions were combined to quantitatively identify heavy metal sources in a suburban agricultural area of Kaifeng, China. Using multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) and ICP-MS, we measured Pb, Zn and Cu stable isotopic compositions, HM concentrations and HM chemical fractions in studied soils, as well as potential sources around the highly polluted site, including total suspended particle, compound fertilizer, irrigated river water and sediments. The results showed that total contents and chemical fractions of heavy metals, as well as Pb-Zn-Cu isotopic compositions presented great variation in different sites, which implied that heavy metal accumulation was obviously affected by local anthropogenic pollution source. UNMIX and PMF presented good agreement on source apportionment that industrial and agricultural activities (61.74% and 60.75% for UNMIX and PMF, respectively) were the major contributors to heavy metal accumulation in the study area. Especially, sewage irrigation and atmosphere deposition accounted for a large proportion (28.14% and 41.03% for UNMIX and PMF, respectively). Moreover, isotopic compositions of Pb, Zn and Cu in highly polluted soils and environment media gave further confirmation that sewage irrigation and atmosphere deposition were primary anthropogenic source. Therefore, combination of UNMIX, PMF model and Pb-Zn-Cu isotopic compositions showed good coordination in quantitative and specific source identification of heavy metals in agricultural soils.

Depiction of the genomic and genetic landscape identifies CCL5 as a protective factor in colorectal neuroendocrine carcinoma.

BACKGROUND: Colorectal neuroendocrine carcinomas (CRNECs) are highly aggressive tumours with poor prognosis and low incidence. To date, the genomic landscape and molecular pathway alterations have not been elucidated. METHODS: Tissue sections and clinical information of CRNEC (n = 35) and CR neuroendocrine tumours (CRNETs) (n = 25) were collected as an in-house cohort (2010-2020). Comprehensive genomic and expression panels (AmoyDx® Master Panel) were applied to identify the genomic and genetic alterations of CRNEC. Through the depiction of the genomic landscape and transcriptome profile, we compared the difference between CRNEC and CRNET. Reverse transcription-polymerase chain reaction and immunofluorescence staining were performed to confirm the genetic alterations. RESULTS: High tumour mutation load was observed in CRNEC compared with CRNET. CRNECs showed a "cold" immune landscape and increased endothelial cell activity compared with NETs. Importantly, PAX5 was aberrantly expressed in CRNEC and predicted a poor prognosis of CRNECs. CCL5, a factor that is considered an immunosuppressive factor in several tumour types, was strongly expressed in CRNEC patients with long-term survival and correlated with high CD8+ T cell infiltration. CONCLUSION: Through the depiction of the genomic landscape and transcriptome profile, we demonstrated alterations in molecular pathways and potential targets for immunotherapy in CRNEC.

A novel genomic classification system of gastric cancer via integrating multidimensional genomic characteristics.

BACKGROUND: Gastric cancer (GC) is one of the leading causes of cancer deaths with high heterogeneity. There is currently a paucity of clinically applicable molecular classification system to guide precise medicine. METHODS: A total of 70 Chinese patients with GC were included in this study and whole-exome sequencing was performed. Unsupervised clustering was undertaken to identify genomic subgroups, based on mutational signature, copy number variation, neoantigen, clonality, and essential genomic alterations. Subgroups were characterized by clinicopathological factors, molecular features, and prognosis. RESULTS: We identified 32 significantly mutated genes (SMGs), including TP53, ARID1A, PIK3CA, CDH1, and RHOA. Of these, PREX2, PIEZO1, and FSIP2 have not been previously reported in GC. Using a novel genome-based classification method that integrated multidimensional genomic features, we categorized GC into four subtypes with distinct clinical phenotypes and prognosis. Subtype 1, which was predominantly Lauren intestinal type, harbored recurrent TP53 mutation and ERBB2 amplification, high tumor mutation burden (TMB)/tumor neoantigen burden (TNB), and intratumoral heterogeneity, with a liver metastasis tendency. Subtype 2 tended to occur at an elder age, accompanying with frequent TP53 and SYNE1 mutations, high TMB/TNB, and was associated with poor prognosis. Subtype 3 and subtype 4 included patients with mainly diffuse/mixed type tumors, high frequency of peritoneal metastasis, and genomical stability, whereas subtype 4 was associated with a favorable prognosis. CONCLUSIONS: By integrating multidimensional genomic characteristics, we proposed a novel genomic classification system of GC associated with clinical phenotypes and provided a new insight to facilitate genome-guided risk stratification and disease management.

90-gene signature assay for tissue origin diagnosis of brain metastases.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors. 2-14% of BM patients present with unknown primary site despite intensive evaluations. This study aims to evaluate the performance of a 90-gene expression signature in determining the primary sites for BM samples. METHODS: The sequence-based gene expression profiles of 708 primary brain tumors (PBT) collected from The Cancer Genome Atlas (TCGA) database were analyzed by the 90-gene expression signature, with a similarity score for each of 21 common tumor types. We then used Optimal Binning algorithm to generate a threshold for separating PBT from BM. Eighteen PBT samples were analyzed to substantiate the reliability of the threshold. In addition, the performance of the 90-gene expression signature for molecular classification of metastatic brain tumors was validated in a cohort of 48 BM samples with the known origin. For each BM sample, the tumor type with the highest similarity score was considered tissue of origin. When a sample was diagnosed as PBT, but the similarity score below the threshold, the second prediction was considered as the primary site. RESULTS: A threshold of the similarity score, 70, was identified to discriminate PBT from BM (PBT: > 70, BM: ≤ 70) with an accuracy of 99% (703/708, 95% CI 98-100%). The 90-gene expression signature was further validated with 18 PBT and 44 BM samples. The results of 18 PBT samples matched reference diagnosis with a concordance rate of 100%, and all similarity scores were above the threshold. Of 44 BM samples, the 90-gene expression signature accurately predicted primary sites in 89% (39/44, 95% CI 75-96%) of the cases. CONCLUSIONS: Our findings demonstrated the potential that the 90-gene expression signature could serve as a powerful tool for accurately identifying the primary sites of metastatic brain tumors.

[Transurethral holmium laser enucleation of the prostate combined with Jisheng Shenqi Decoction for benign prostatic hyperplasia].

OBJECTIVE: To assess the clinical effects of transurethral holmium laser enucleation of the prostate (HoLEP) combined with Jisheng Shenqi Decoction (HoLEP + JSSD) on BPH. METHODS: This study included 110 BPH patients treated in our hospital from August 2017 to April 2018, who were randomly assigned to receive HoLEP (n = 55) or HoLEP + JSSD (n = 55). We compared the pre- and post-operative IPSS, quality of life (QOL) score, prostate volume, postvoid residual urine volume (PVR), maximum urinary flow rate (Qmax), average urinary flow rate (Qavg) and levels of serum T, E2 and T/E2 as well as postoperative complications between the two groups of patients. RESULTS: After treatment, both IPSS and QOL score were significantly lower in the HoLEP + JSSD than in the HoLEP group (P < 0.05), and so were the prostate volume and PVR (P < 0.05). The Qmax, Qavg and serum T level were significantly higher (P < 0.05) while T/E2 markedly lower in the former than in the latter group (P < 0.05). There were no statistically significant differences between the HoLEP + JSSD and HoLEP groups in the E2 level (P > 0.05) or the total incidence rate of complications postoperatively (21.82% vs 29.09%, P > 0.05). CONCLUSIONS: HoLEP + JSSD can significantly alleviate the lower urinary tract symptoms as well as improve the QOL and bladder and urinary tract functions of BPH patients.

Physical interaction between human ribonucleotide reductase large subunit and thioredoxin increases colorectal cancer malignancy.

Ribonucleotide reductase (RR) is the rate-limiting enzyme in DNA synthesis, catalyzing the reduction of ribonucleotides to deoxyribonucleotides. During each enzymatic turnover, reduction of the active site disulfide in the catalytic large subunit is performed by a pair of shuttle cysteine residues in its C-terminal tail. Thioredoxin (Trx) and glutaredoxin (Grx) are ubiquitous redox proteins, catalyzing thiol-disulfide exchange reactions. Here, immunohistochemical examination of clinical colorectal cancer (CRC) specimens revealed that human thioredoxin1 (hTrx1), but not human glutaredoxin1 (hGrx1), was up-regulated along with human RR large subunit (RRM1) in cancer tissues, and the expression levels of both proteins were correlated with cancer malignancy stage. Ectopically expressed hTrx1 significantly increased RR activity, DNA synthesis, and cell proliferation and migration. Importantly, inhibition of both hTrx1 and RRM1 produced a synergistic anticancer effect in CRC cells and xenograft mice. Furthermore, hTrx1 rather than hGrx1 was the efficient reductase for RRM1 regeneration. We also observed a direct protein-protein interaction between RRM1 and hTrx1 in CRC cells. Interestingly, besides the known two conserved cysteines, a third cysteine (Cys779) in the RRM1 C terminus was essential for RRM1 regeneration and binding to hTrx1, whereas both Cys32 and Cys35 in hTrx1 played a counterpart role. Our findings suggest that the up-regulated RRM1 and hTrx1 in CRC directly interact with each other and promote RR activity, resulting in enhanced DNA synthesis and cancer malignancy. We propose that the RRM1-hTrx1 interaction might be a novel potential therapeutic target for cancer treatment.

A naive Bayes algorithm for tissue origin diagnosis (TOD-Bayes) of synchronous multifocal tumors in the hepatobiliary and pancreatic system.

Synchronous multifocal tumors are common in the hepatobiliary and pancreatic system but because of similarities in their histological features, oncologists have difficulty in identifying their precise tissue clonal origin through routine histopathological methods. To address this problem and assist in more precise diagnosis, we developed a computational approach for tissue origin diagnosis based on naive Bayes algorithm (TOD-Bayes) using ubiquitous RNA-Seq data. Massive tissue-specific RNA-Seq data sets were first obtained from The Cancer Genome Atlas (TCGA) and ∼1,000 feature genes were used to train and validate the TOD-Bayes algorithm. The accuracy of the model was >95% based on tenfold cross validation by the data from TCGA. A total of 18 clinical cancer samples (including six negative controls) with definitive tissue origin were subsequently used for external validation and 17 of the 18 samples were classified correctly in our study (94.4%). Furthermore, we included as cases studies seven tumor samples, taken from two individuals who suffered from synchronous multifocal tumors across tissues, where the efforts to make a definitive primary cancer diagnosis by traditional diagnostic methods had failed. Using our TOD-Bayes analysis, the two clinical test cases were successfully diagnosed as pancreatic cancer (PC) and cholangiocarcinoma (CC), respectively, in agreement with their clinical outcomes. Based on our findings, we believe that the TOD-Bayes algorithm is a powerful novel methodology to accurately identify the tissue origin of synchronous multifocal tumors of unknown primary cancers using RNA-Seq data and an important step toward more precision-based medicine in cancer diagnosis and treatment.

Serum thyroid hormone levels among Chinese pregnant women.

AIM: The aim of this study is to examine gestational serum thyroid hormone levels and influencing factors among Chinese pregnant women with high dietary iodine intake. METHODS: The study was conducted from 2011 and 2013 in Zhoushan Women & Children's Hospital, Zhejiang, China. A total of 1991 pregnant women were enrolled and their serum levels of free thyroid hormones (FT4, FT3, and TSH) were detected by chemiluminescence method. RESULTS: Gestational serum FT4 and FT3 decreased with gestational week while TSH increased. Furthermore, the prevalence rate of subclinical hypothyroid increased with gestational stages, especially in the third trimester. Women aged more than 30 years had lower FT4 and FT3 in the first trimester and lower FT4 in the second trimester. No significant difference was found in the association of gestational serum thyroid hormones with maternal height and the gender of fetuses. CONCLUSION: Gestational serum thyroid hormones significantly changed with gestational week and were associated with the age of women. Specific normal range of thyroid hormones might be modified so as to better evaluate the thyroid hormone levels of pregnant women during pregnancy.

A retrospective study of adjuvant albumin-bound paclitaxel plus S-1 after D2 gastrectomy versus oxaliplatin plus S-1 in gastric cancer.

Adjuvant oxaliplatin plus S-1 (SOX) chemotherapy for gastric cancer (GC) after D2 gastrectomy has been proven effective. There has yet to be a study that evaluates adjuvant nanoparticle albumin-bound paclitaxel (nab-paclitaxel) plus S-1. In this single-center, retrospective study, GC patients after D2 gastrectomy received either nab-paclitaxel plus S-1 (AS group) or SOX group were recruited between January 2018 and December 2020 in The First Affiliated Hospital of Zhejiang University. Intravenous nab-paclitaxel 120 mg/m2 or 260 mg/m2 and oxaliplatin 130 mg/m2 were administered as eight 3 week cycle, especially in the AS and SOX group. Patients received S-1 twice daily with a dose of 40 mg/m2 in the two groups on days 1-14 of each cycle. The end points were disease-free survival (DFS) rate at 3 years and adverse events (AEs). There were 56 eligible patients, 28 in the AS group and 35 in the SOX group. The 3 year DFS rate was 78.0% in AS group versus 70.7% in SOX group (p = 0.46). Subgroup analysis showed that the patients with signet-ring positive in the AS group had a prolonged DFS compared with the SOX group (40.0 vs. 13.8 m, p = 0.02). The diffuse-type GC or low differentiation in the AS group was associated with numerically prolonged DFS compared with the SOX group, but the association was not statistically significant (p = 0.27 and p = 0.15 especially). Leukopenia (14.3%) were the most prevalent AEs in the AS group, while thrombocytopenia (28.5%) in the SOX group. Neutropenia (7.1% in AS group) and thrombocytopenia (22.8% in SOX group) were the most common grade 3 or 4 AEs. In this study analyzing past data, a tendency towards a greater 3 year DFS was observed when using AS regimen in signet-ring positive patients. AS group had fewer thrombocytopenia compared to SOX group. More studies should be conducted with larger sample sizes.

The combination of exon sequencing and metabolomics to establish a molecular typing system for gastric cancer.

Background: Gastric cancer (GC) is one of the most common malignant tumors in the world. It has become increasingly difficult to meet the needs of precision therapy using the existing molecular typing system. Therefore, developing a more effective molecular typing system for GC is urgent. Methods: In this study, 100 Chinese GC patients were included. Whole-exome sequencing (WES) and metabolomics analysis were performed to reveal the characteristics of genomic and metabolic changes. Results: In WES, nonsynonymous mutations accounted for the majority. Based on metabolomics, GC has been divided into three subtypes with distinct metabolic features. Importantly, we ultimately divided GC into four subtypes with different metabolic characteristics, genomic alterations, and clinical prognoses by incorporating biomics analysis. Conclusions: Integrating biological features, we constructed a novel molecular system for GC that was closely related to genetics and metabolism, providing new insights for further understanding the heterogeneity and formulating precise treatment strategies.

Stem cell landscape aids in tumor microenvironment identification and selection of therapeutic agents in gastric cancer.

Gastric cancer stem cells (GCSCs) are strongly associated with the refractory characteristics of gastric cancer, including drug resistance, recurrence, and metastasis. The prognosis for advanced gastric cancer patients treated with multimodal therapy after surgery remains discouraging. GCSCs hold promise as therapeutic targets for GC patients. We obtained 26 sets of stem cell-related genes from the StemChecker database. The Consensus clustering algorithm was employed to discern three distinct stemness subtypes. Prognostic outcomes, components of the tumor microenvironment (TME), and responses to therapies were compared among these subtypes. Following this, a stemness-risk model was formulated using weighted gene correlation network analysis (WGCNA), alongside Cox regression and random survival forest analyses. The C2 subtype predominantly showed enrichment in negative prognostic CSC gene sets and demonstrated an immunosuppressive TME. This specific subtype exhibited minimal responsiveness to immunotherapies and demonstrated reduced sensitivity to drugs. Four pivotal genes were integrated into the construction of the stemness model. Gastric cancer patients with higher stemness-risk scores demonstrated poorer prognoses, a greater presence of immunosuppressive components in TME, and lower rates of treatment response. Subset analysis indicated that only the low-stemness risk subtype derives benefit from 5-fluorouracil-based adjuvant chemotherapy. The model's effectiveness in immunotherapeutic prediction was further validated in the PRJEB25780 cohort. Our study categorized gastric cancer patients into three stemness subtypes, each demonstrating distinct prognoses, components of TME infiltration, and varying sensitivity or resistance to standard chemotherapy or targeted therapy. We propose that the stemness risk model may help the development of well-grounded treatment recommendations and prognostic assessments.

A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer.

Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor microenvironment (TME) has been characterized well at single-cell resolution. However, a spatial interaction map of the CRC TME is still elusive. Here, we integrate multiomics analyses and establish a spatial interaction map to improve the prognosis, prediction, and therapeutic development for CRC. We construct a CRC immune module (CCIM) that comprises FOLR2+ macrophages, exhausted CD8+ T cells, tolerant CD8+ T cells, exhausted CD4+ T cells, and regulatory T cells. Multiplex immunohistochemistry is performed to depict the CCIM. Based on this, we utilize advanced deep learning technology to establish a spatial interaction map and predict chemotherapy response. CCIM-Net is constructed, which demonstrates good predictive performance for chemotherapy response in both the training and testing cohorts. Lastly, targeting FOLR2+ macrophage therapeutics is used to disrupt the immunosuppressive CCIM and enhance the chemotherapy response in vivo.

Insights into As accumulation in soil-groundwater-wheat-hair system of suburban farmland: Distribution, transfer and potential health risk.

Health risks caused by arsenic (As) contamination in soils and its migration in environmental media have attracted much attention. In this study, suburban farmland of KF city in the ecotone of the Yellow River and Huaihe River Basin was taken as the research area. A series of samples including topsoils (246), profile soils (280), matched wheat grains (22 groups), groundwater (26) and human hair (355) were collected. As distribution and transfer in soil-groundwater-wheat-hair (SGWH) system in typical sites were explored, and comprehensive health risk of As in SGWH system was assessed based on US EPA model and local exposure parameters. The results showed that spatial distribution of total As presented a significant high value area, and higher As contents (in the range of 0.45-29.86 mg kg-1) and bioavailability was mainly in topsoils, which indicated that anthropogenic sources have led to As enrichment in studied area. Also, it was found that the As contents in 95 % of wheat grain samples were higher than that in the control soils, and 9 % groundwater samples were above national Class I standards. Especially, average As content in hair in typical sites was obviously influenced by that in soil, wheat and groundwater. Moreover, As migration curve along soil → wheat (groundwater) → hair appeared an irregular 'V' shape, and transfer coefficients of Tf water/soil (10-5), Tf wheat/soil (10-3), Tf hair/soil (10-2), Tf hair/wheat (101) and Tf hair/water (104) presented an obvious increasing trend of magnitude, implying that human body has a higher As enrichment risk. Furthermore, comprehensive health risks for children and adults in typical sites were significant, while wheat is the main risk medium. In general, arsenic accumulation in human hair is good consistent with EPA health risk model, and their combination can better evaluate environmental exposure risk of As.

The Memorial Sloan Kettering Prognostic Score: Correlation with survival in patients with advanced gastric cancer.

BACKGROUND: Notwithstanding that the past decade has witnessed unprecedented medical progress, gastric cancer (GC) remains a leading cause of cancer death, highlighting the need for effective prognostic markers. The Memorial Sloan Kettering Prognostic Score (MPS) has been validated as a valuable prognostic tool for patients with metastatic pancreatic adenocarcinoma (mPDAC). This study aimed to assess the prognostic value of the MPS in advanced GC. METHODS: Data from 367 patients were analyzed in the present study. The MPS for each patient was calculated based on the sum of scores based on the neutrophil-to-lymphocyte ratio and serum albumin levels. Multivariate analyses were performed to identify the independent clinicopathological parameters associated with overall survival (OS). Further subgroup analyses based on clinicopathological features were conducted. RESULTS: Patients with MPS 0 (n = 161), MPS 1 (n = 158), and MPS 2 (n = 48) exhibited significantly different OS, with a median survival duration of 20.7 (95%CI: 12.2-29.2), 14.9 (95%CI: 12.5-17.3), and 12.7 (95%CI: 9.3-16.0) months, respectively (p < 0.001). Significant differences in survival were observed among different groups of patients receiving chemotherapy (18.5 months vs. 14.7 months vs. 11.0 months, p = 0.03) or the subgroup receiving chemotherapy plus immunotherapy as first-line treatment (32.6 months vs. 17.7 months vs. 12.7 months, p = 0.02). The MPS was identified as an independent prognostic factor in multivariate analysis. During subgroup analyses, MPS-low (MPS 0) was consistently associated with a better prognosis than MPS-high (MPS 1 or 2). CONCLUSIONS: MPS is a practical, simple, and useful prognostic tool for patients with advanced GC. Further studies are warranted to validate its prognostic value in advanced GC.