Serum Glucose-6-Phosphate Dehydrogenase Activity as a Biomarker for Gastric Cancer Stage Prediction.

Emerging evidences indicate that dysregulated long noncoding RNAs (lncRNAs) are implicated in cancer tumorigenesis and progression and might be used as diagnosis and prognosis biomarker, or potential therapeutic targets. LncRNA PVT1 has been reported to be upregulated in diverse human cancers; however, its clinical significance in gastric cancer (GC) remains elusive. This study was to evaluate the expression of PVT1 in GC and further explore its clinical significance.Previous microarray datasets were analyzed to conduct apreliminary screening for candidate lncRNAs of gastric cancer biomarkers in human gastric cancer tissues. Expression levels of PVT1 in 111pairs of gastric cancer and adjacent normal tissues, gastric cancer cell lines and gastric cancer juices compared to their corresponding controls were detected by real-time quantitative RT-PCR assay. Areceiver operating characteristic (ROC) curve and Kaplan-Meier analysis were constructed to evaluate the diagnostic and prognostic values. Univariate and multivariate analysis were performed using the Cox proportional hazard analysis.PVT1 expression was remarkably increased in gastric cancer tissues and cell lines compared with that in the normal control, and its up-regulation was significantly correlated to invasion depth (P < 0.001), advanced TNM stage (P = 0.002) and regional lymph nodes metastasis (P < 0.001) in gastric cancer. PVT1 levels were robust in differentiating gastric cancer tissues from controls [area under the curve (AUC) = 0.728; 95 % confidence interval (CI) = 0.665-0.786, p<0.01]. Kaplan-Meier analysis demonstrated that increased PVT1 expression contributed to poor overall survival (P < 0.01) and disease-free survival (P < 0.01) of patients. Amultivariate survival analysis also indicated that PVT1 could be an independent prognostic marker. The levels of PVT1 in gastric juice from gastric patients were significantly higher than those from normal subjects (P = 0.03). PVT1 might serve as apromising biomarker for early detection and prognosis prediction of gastric cancer.

IntroductionThe platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII) are markers for systemic inflammatory responses and have been shown by numerous studies to correlate with the prognosis of gastric cancer (GC). However, the diagnostic value of these three markers in GC is unclear, and no research has examined them in combination. In this study, we investigated the value of the PLR, NLR, and SII individually or in combination for GC diagnosis and elucidated the connection of these three markers with GC patients’ clinicopathological features.MethodsThis retrospective study was conducted on 125 patients diagnosed with GC and 125 healthy individuals, whose peripheral blood samples were obtained for analysis. The preoperative PLR, NLR, and SII values were subsequently calculated.ResultsThe results suggest that the PLR, NLR, and SII values of the GC group were considerably higher than those of the healthy group (all P ≤ 0.001); moreover, all three parameters were notably higher in early GC patients (stage I/II) than in the healthy population. The diagnostic value of each index for GC was analyzed using receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) calculation. The diagnostic efficacy of the SII alone (AUC: 0.831; 95% confidence interval [CI], 0.777–0.885) was expressively better than those of the NLR (AUC: 0.821; 95% CI: 0.769–0.873, P = 0.017) and PLR (AUC: 0.783; 95% CI: 0.726–0.840; P = 0.020). The AUC value of the combination of the PLR, NLR, and SII (AUC: 0.843; 95% CI: 0.791–0.885) was significantly higher than that of the combination of the SII and NLR (0.837, 95% CI: 0.785–0.880, P≤0.05), PLR (P = 0.020), NLR (P = 0.017), or SII alone (P ≤ 0.001). The optimal cut-off values were determined for the PLR, NLR, and SII using ROC analysis (SII: 438.7; NLR: 2.1; PLR: 139.5). Additionally, the PLR, NLR, and SII values were all meaningfully connected with the tumor size, TNM stage, lymph node metastasis, and serosa invasion (all P ≤ 0.05). Elevated levels of the NLR and SII were linked to distant metastasis (all P ≤ 0.001).DiscussionThese data suggest that the preoperative PLR, NLR, and SII could thus be utilized as diagnostic markers for GC or even early GC. Among these three indicators, the SII had the best diagnostic efficacy for GC, and the combination of the three could further improve diagnostic efficiency.

This study was conducted to develop a novel algorithm for determining the origin of tumors by combining analysis of cluster patterns with immunocytochemistry (ICC) for markers in cells from fine-needle aspirates of ascites. We used LBC, based on SurePathTM (BD Diagnostics) technology, to screen 96 peritoneal fluid samples from patients with known malignancies and from 10 control patients with cirrhosis. Following dual ICC staining for cytokeratin 7 (CK7) and paired box gene 8 (PAX8), we developed an algorithm using immunoreactivity and three-dimensional (3D) cluster patterns to correlate staining and 3D cluster patterns with common primary origins that included stomach, ovarian, pancreatobiliary tract, colon, lung, and breast cancers. With the application of an automatic digitalized image analyzer, competence performance was analyzed using receiver operating characteristics (ROC) curve analysis. CK7 and PAX8 staining and 3D cluster patterns were used to differentiate primary origins. Samples from patients with stomach cancer were no 3D cluster /CK7+/PAX8- with area under the curve (AUC) of 0.8699 in ROC curve analysis. Samples from ovarian cancer patients were large 3D cluster/CK7+/PAX8+ with AUC of 0.9812. Samples from pancreatobiliary tract cancer patients were small 3D cluster/CK7+/PAX8- with AUC of 0.8772. The remaining cancer samples, including breast, lung and colon cancer samples, had similar patterns of large 3D clusters/CK7+/PAX8- with AUC of 0.882, especially for lung cancer. SurePathTM technology, using 3D cluster patterns and dual ICC for CK7 and PAX8 in peritoneal fluid samples, can provide important information for determining specific primary origins in cases of unknown primary carcinoma.

Objective To investigate the clinical value of combined detection of serum pepsinogen (PG)Ⅰ, PGⅡ, PGⅠ/PGⅡ (PGR), gastrin-17 (G-17) and IgG anti-Helicobacter Pylori (IgG anti-Hp) in the diagnosis of early gastric cancer. Methods One hundred and twenty patients with gastric cancer (early gastric cancer group), 60 patients with atrophic gastritis (atrophic gastritis group) and 120 healthy volunteers (control group) who were examined or treated in our hospital from January 2018 to June 2019 were selected as the subjects. The levels of serum PGⅠ, PGⅡ, PGR, G-17 and IgG anti-Hp were compared among the three groups. The indicators and combined diagnostic value were analyzed by receiver operating characteristic (ROC) curve. Results The levels of PGⅠ in early gastric cancer group, atrophic gastritis group and control group were (59.85±8.59)ng/ml, (72.19±9.89)ng/ml, (96.83±8.66)ng/ml, with statistically significant difference (F=530.504, P<0.001). The levels of PGⅡ in the three groups were (23.19±2.45)ng/ml, (20.60±4.19)ng/ml, (16.52±3.34)ng/ml, with statistically significant difference (F=130.085, P<0.001). The levels of PGR in three groups were 2.78±0.69, 4.33±0.95, 6.21±1.46, with statistically significant difference (F=288.801, P<0.001). The levels of G-17 in the three groups were (77.04±10.09)ng/ml, (64.69±7.22)ng/ml, (55.91±8.32)ng/ml, with statistically significant difference (F=170.770, P<0.001). The levels of IgG anti-Hp in the three groups were (70.23±8.11)IU, (58.30±9.37)IU, (33.00±5.24)IU, with statistically significant difference (F=778.431, P<0.001). The levels of serum PGⅠand PGR in early gastric cancer group and atrophic gastritis group were significantly lower than those in control group (all P<0.05). The levels of serum PGⅠand PGR in early gastric cancer group were significantly lower than those in atrophic gastritis group (both P<0.05). While serum PGⅡ, G-17 and IgG anti-Hp in early gastric cancer group and atrophic gastritis group were significantly higher than those in control group (all P<0.05). The levels of PGⅡ, G-17 and IgG anti-Hp in gastric cancer group were significantly higher than those in atrophic gastritis group (all P<0.05). According to the ROC curve, the critical value of serum PGⅠ diagnosis was 73.11 ng/ml, the sensitivity was 63.33%, the specificity was 83.33%, and the area under the curve (AUC) was 0.801. The critical value of serum PGⅡ diagnosis was 19.55 ng/ml, the sensitivity was 75.83%, the specificity was 72.22%, and the AUC was 0.760. The critical value of serum PGR diagnosis was 4.60, the sensitivity was 82.50%, the specificity was 77.22%, and the AUC was 0.816. The critical value of serum G-17 diagnosis was 64.33 ng/ml, the sensitivity was 64.17%, the specificity was 65.56%, and the AUC was 0.631. The critical value of IgG anti-Hp diagnosis was 53.80 IU, the sensitivity was 59.17%, the specificity was 75.00%, and the AUC was 0.708. At the critical tangent point, the sensitivity, specificity and AUC of PG I + IgG anti-Hp were 69.17%, 76.67% and 0.754 respectively; the sensitivity, specificity and AUC of PGR + IgG anti-Hp were 88.33%, 74.44% and 0.798 respectively; the sensitivity, specificity and AUC of G-17 + IgG anti-Hp were 71.67%, 65.56% and 0.718 respectively. The sensitivity of joint detection of the five indexes was 92.50%, the specificity was 72.22%, and the AUC was 0.869. The sensitivity of joint detection was significantly higher than that of individual detection (all P<0.05), and the AUC of joint detection was significantly higher than that of individual indexes (Z=1.848, P=0.032; Z=3.145, P=0.001; Z=1.688, P=0.046; Z=7.726, P<0.001; Z=4.931, P<0.001; Z=3.188, P=0.001; Z=1.783, P=0.037; Z=4.534, P<0.001). Conclusion The combined detection of serum PGⅠ, PGⅡ, PGR, G-17 and IgG anti-Hp can improve the sensitivity of gastric cancer diagnosis and it is of great significance and value for early diagnosis of gastric cancer. Key words: Stomach neoplasms; Pepsinogens; Helicobacter Pylori; Gastrin-17

Gastric cancer is the second cause of cancer deaths in China. To identify potential markers for screening or diagnosis of gastric cancer, we coupled xenotransplantation mouse models with a urine metabolomic approach. SGC-7901 gastric cancer cells were subcutaneously or orthotopically implanted into nude mice to establish metastasis and non-metastasis mouse models. Urine samples from mice bearing tumors or gastric cancer patients and their healthy controls were collected and subjected to gas chromatography and mass spectrometry (GC/MS) analysis. Metabolic data were analyzed using Mann-Whitney test to find urinary biomarkers for gastric cancer. Diagnostic models for gastric cancer mice and patients were constructed using principal components analysis (PCA) and validated with the area under the curve (AUC) of receiver operating characteristic (ROC) curves. The results indicated these metabolites mainly include lactic acid, serine, proline, malic acid, and fatty acids. The PCA models discriminated all gastric cancer mice or most gastric cancer patients including six of seven early stage patients, from their healthy controls with AUC value of 1.0 or 0.996, respectively. In addition, they were able to differentiate between metastatic and non-metastatic mice with AUC value of 1.0, as well as between invasive/metastatic and non-invasive cancers with AUC value of 0.982. Our data suggest that there are significant metabolic alterations during progression of gastric cancer and the potential metabolic biomarkers could be useful for screening and early diagnosis of gastric cancer progression.

The neutrophil-lymphocyte ratio (NLR) and the platelet-lymphocyte ratio (PLR) are markers of systemic inflammation. However, there is little evidence of the value of inflammation in the early diagnosis of gastric cancer (GC). A total of 2,606 patients diagnosed with GC in the past three years and 3,219 healthy controls over the same period were included in this study. Peripheral blood samples were obtained to analyze the NLR, PLR, carcinoembryonic antigen (CEA), and carbohydrate antigen 19-9 (CA19-9). The optimal cutoff levels for the NLR and PLR were defined by receiver operating characteristic (ROC) curve analysis (NLR = 2.258, PLR = 147.368). The value of different biomarkers for diagnosing GC was compared by the area under the curve (AUC). The NLR and PLR showed diagnostic sensitivity in GC (AUC = 0.715, AUC = 0.707). Using the Bonferroni correction, the NLR and PLR were superior to CEA and CA19-9 in the diagnosis of GC (P < 0.0001). The systemic inflammatory markers were significantly higher in the early stage of GC than tumor markers. After grouping patients and healthy controls by gender, we found that the diagnostic significance of combined NLR and PLR for GC was greater in male patients than in female patients (P < 0.0001). The diagnostic value of the NLR and PLR in GC is higher than that of the traditional tumor markers CEA and CA19-9. Systemic markers of inflammation are more valuable in male than female patients.

Patients with gastric cancer (GC) are usually first diagnosed at an advanced stage due to the absence of obvious symptoms at an early GC (EGC) stage. Therefore, it is necessary to identify an effective screening method to detect precursor lesions of GC (PLGC) and EGC to increase the 5-year survival rate of patients. Cell-free RNA, as a biomarker, has shown potential in early diagnosis, personalised treatment, and prognosis of cancer. In this study, six RNAs (CEBPA-AS1, INHBA-AS1, AK001058, UCA1, PPBP, and RGS18) were analysed via real-time quantitative polymerase chain reaction (RT-qPCR) using the plasma of patients with EGC and PLGC to identify diagnostic biomarkers. The receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic accuracy. Among the six RNAs, four lncRNAs (CEBPA-AS1, INHBA-AS1, AK001058, and UCA1) were upregulated and two mRNAs (PPBP and RGS18) were downregulated in the plasma of patients with PLGC and EGC. According to the findings of the ROC analysis, the four-RNA combination of INHBA-AS1, AK001058, UCA1, and RGS18 had the highest area under the curve (AUC) value for determining risk of GC in patients with PLGC and the six-RNA combination including CEBPA-AS1, INHBA-AS1, AK001058, UCA1, PPBP, and RGS18 had the highest AUC value for determining the risk of GC in patients with EGC. The results suggest the potential usefulness of noninvasive biomarkers for the molecular diagnosis of GC at earlier stages.

Impacts of the Coronavirus 2019 Pandemic on Gastrointestinal Endoscopy Volume and Diagnosis of Gastric and Colorectal Cancers: A Population-Based Study

H19 is one of the long non-coding RNAs (LncRNA) that is related to the progression of many diseases including cancers. This work was carried out to study the level of the long non-coding RNA; H19, in plasma of patients with gastric cancer (GC) and to assess its significance in their clinical management. Sixty-two participants were enrolled in the present study. The first group included 32 GC patients. The second group was formed of 30 age and sex matched healthy volunteers serving as a control group. Plasma samples were used to assess H19 gene expression using real-time quantitative PCR technique. H19 expression was up-regulated and closely related to TNM cancer stages in GC patients. Using Receiver Operating Characteristic (ROC) curve analysis, a cutoff level of 0.5 was set for H19 expression to diagnose GC cases achieving a sensitivity of 68.75%, specificity of 56.67%, positive predictive value (PPV) 62.86% and negative predictive value (NPV) 62.96% with an area under the curve (AUC) of 72.4%. Combined use of Carcinoembryonic Antigen (CEA) and H19 level in GC diagnosis was evaluated using ROC curve revealing improvement in performance with an area under the curve of 80.4%. Up-regulation of H19 is closely associated with gastric cancer displaying progressive up-regulation in advanced stages of the disease implementing its role as a potential non-invasive diagnostic biomarker in gastric cancer and as a novel tool in gastric cancer management with better performance achieved on using both CEA and H19 simultaneously.

BACKGROUNDThe level of Ki-67 expression has served as a prognostic factor in gastric cancer. The quantitative parameters based on the novel dual-layer spectral detector computed tomography (DLSDCT) in discriminating the Ki-67 expression status are unclear.AIMTo investigate the diagnostic ability of DLSDCT-derived parameters for Ki-67 expression status in gastric carcinoma (GC).METHODSDual-phase enhanced abdominal DLSDCT was performed preoperatively in 108 patients with gastric adenocarcinoma. Primary tumor monoenergetic CT attenuation value at 40-100 kilo electron volt (kev), the slope of the spectral curve (λHU), iodine concentration (IC), normalized IC (nIC), effective atomic number (Zeff) and normalized Zeff (nZeff) in the arterial phase (AP) and venous phase (VP) were retrospectively compared between patients with low and high Ki-67 expression in gastric adenocarcinoma. Spearman’s correlation coefficient was used to analyze the association between the above parameters and Ki-67 expression status. Receiver operating characteristic (ROC) curve analysis was performed to compare the diagnostic efficacy of the statistically significant parameters between two groups.RESULTSThirty-seven and 71 patients were classified as having low and high Ki-67 expression, respectively. CT40 kev-VP, CT70 kev-VP, CT100 kev-VP, and Zeff-related parameters were significantly higher, but IC-related parameters were lower in the group with low Ki-67 expression status than the group with high Ki-67 expression status, and other analyzed parameters showed no statistical difference between the two groups. Spearman’s correlation analysis showed that CT40 kev-VP, CT70 kev-VP, CT100 kev-VP, Zeff, and nZeff exhibited a negative correlation with Ki-67 status, whereas IC and nIC had positive correlation with Ki-67 status. The ROC analysis demonstrated that the multi-variable model of spectral parameters performed well in identifying the Ki-67 status [area under the curve (AUC) = 0.967; sensitivity 95.77%; specificity 91.89%)]. Nevertheless, the differentiating capabilities of single-variable model were moderate (AUC value 0.630 - 0.835). In addition, the nZeffVP and nICVP (AUC 0.835 and 0.805) showed better performance than CT40 kev-VP, CT70 kev-VP and CT100 kev-VP (AUC 0.630, 0.631 and 0.662) in discriminating the Ki-67 status.CONCLUSIONQuantitative spectral parameters are feasible to distinguish low and high Ki-67 expression in gastric adenocarcinoma. Zeff and IC may be useful parameters for evaluating the Ki-67 expression.

Diagnostic values of neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in second primary cancers with a gastric primary cancer

We aimed to determine whether complete blood count(CBC) parameters, such as the white blood count(WBC), hemoglobin(Hb), platelet(PLT), red cell distribution width(RDW), mean platelet volume(MPV), platelet distribution width(PDW), neutrophil-to-lymphocyte ratio(NLR), platelet-to-lymphocyte ratio(PLR), and monocyte-to-lymphocyte ratio(MLR), have a predictive value in the detection of gastric cancer(GC) and intestinal metaplasia(IM). While proven GC, IM, and healthy control(HC) patients were included, patients with the comorbid disease were excluded, and univariate analyses compared three groups. The receiver operating characteristic(ROC) curve analysis was run for CBC parameters. The area under the curve(AUC) was evaluated, and a cut-off value was determined. The sensitivity and specificity of each parameter were considered. The GC, IM, and HC groups consisted of 72(33%), 73(34%), and 72(33%) patients, respectively. RDW, PLT, NLR, PLR, and MLR were significant between GC and IM. The highest AUC (0.727) was obtained for the PLT yielding a 56.9% sensitivity and 79.4% specificity at a cut-off value of 151.8. The AUC of RDW was found as 0.691 and 0.626 for pairwise comparisons of GC-HC and IM-HC, respectively. At a cut-off value of 13.4, PLR yielded 70.8% sensitivity and 61.1% specificity in the detection of GC, while 64.4% sensitivity and 51.1% specificity for IM. CBC parameters, such as RDW, PLT, NLR, PLR, and MLR, have value in detecting GC. RDW also has diagnostic value in helping to detect IM. PLR can help to distinguish patients with GC from those with IM. These inexpensive, easily accessible parameters may help in the timely diagnosis of GC and IM.

Altered microRNA (miRNA) associated with gastric cancer (GC) development and miR-17 and miR-106b were differentially expressed in GC tissues. This study detected serum levels of miR-17 and miR-106b expression in GC, benign gastric disease (BGD) and healthy controls to assess them as tumor markers for GC. Serum samples from 40 GC, 32 BGD (10 gastric ulcer, 14 gastric polyps, and 8 gastric ulcer with polyps) and 36 healthy individuals were subjected to quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis of miR-17 and miR-106b expression. The data showed that the serum levels of miR-17 and miR-106b were significantly reduced in healthy individuals and BGD patients compared to GC patients. There was a significant association of miR-17 and miR-106b expression with age, but not with other clinicopathological features, such as gender, tumor differentiation, stage and lymphatic metastasis. Further analysis showed that, in discriminating GC patients from healthy controls, miR-17 could yield a receiver-operating characteristic (ROC) area under the curve (AUC) of 0.879 with 80.6% sensitivity and 87.5% specificity and miR-106b could yield an AUC of 0.856 with 75.0% sensitivity and 92.5% specificity. The combined AUC of miR-17 and miR-106b was 0.913 with 83.3% sensitivity and 87.5% specificity. Collectively, these data suggest that detection of serum miR-17 and miR-106b levels should be further evaluated as novel non-invasive biomarkers in early GC detection and surveillance of disease progression.

The purpose of this study was to determine whether lysyl oxidase (LOX) is a useful marker of metastasis in gastric cancer (GC) patients in combination with tumor markers carcino-embryonic antigen (CEA), carbohydrate antigen 724 (CA724), carbohydrate antigen 19-9 (CA19-9), and carbohydrate antigen 125 (CA125). There were 215 GC patients (67 without metastasis, 102 with lymph node metastasis, and 46 with peritoneal metastasis) who presented to the Affiliated Cancer Hospital of Guangxi Medical University between May 2009 and November 2012 that were enrolled in this study. The LOX expression level and the serum concentration of the four tumor markers were evaluated preoperatively. All patients underwent computed tomography (CT) and ultrasonography (US) before surgery. Statistical analysis, including receiver operating characteristic (ROC) curve analysis, area under the curve (AUC) analysis, and logistic regression analysis, was performed to evaluate the diagnostic value of these markers in predicting metastasis in GC. For predicting lymph node metastasis in GC, the sensitivity of LOX, CEA, CA724, CA199, and CA125 was 44.12, 12.75, 21.57, 23.53, and 15.69 %, respectively, and increased to 79.41 % in combination. For predicting peritoneal metastasis in GC, the sensitivity of these markers was 56.52, 23.91, 34.78, 36.96, and 34.78 %, respectively, and increased to 91.30 % in combination. Combining LOX with CEA, CA724, CA199, and CA125 could increase the sensitivity of predicting lymph nodes metastasis and peritoneal metastasis in GC. Surgeons can use these markers to determine the best treatment options for patients. Additional large-scale, prospective, multicenter studies are urgently needed to further confirm the results of this study.

BackgroundThe roles of p53 and HER2 in gastric adenocarcinoma (GAC) have been extensively studied; nevertheless, the contribution of mitochondrial transcription factor A (TFAM) remains unclear. Concerning TFAM’s pivotal role in mitochondrial biogenesis, this study aimed to evaluate the TFAM expression in GAC and to assess its associations with p53 and HER2 expressions and clinicopathological outcomes.MethodsWe retrospectively analyzed 77 GAC patients who underwent upfront gastrectomy at Taipei Hospital between 2012 and 2021. Their clinicopathological profiles were recorded in detail. Immunohistochemical (IHC) staining for TFAM, p53, and HER2 protein expressions was semiquantified using IHC pixelwise H-score analyzed by ImageJ plugins IHC profiler. Associations between two continuous variables were assessed by Spearman’s correlation coefficient (CC), and trendlines were fitted using SPSS’s curve estimation function. The optimal cutoff for survival discrimination was derived from receiver operating characteristic (ROC) curve analysis by selecting the threshold with the highest Youden index and area under the curve (AUC). Prognostic variables with a Log-rank test p-value ≤ 0.1 were entered into a multi-variate Cox proportional hazards regression (Cox regression) model to identify independent ones and their relative hazards ratio (HR).ResultsTFAM IHC pixelwise H-score was significantly associated with advanced T and N status, lymphovascular invasion, perineural invasion and poor differentiation (all’s p < 0.05), and was inversely correlated with tumor size (Spearman’s rho CC = -0.402, p < 0.001) in a logarithmic distribution (p < 0.001). A positive correlation (Spearman’s rho CC = 0.312, p = 0.006) in cubic distribution (p < 0.001) was observed between p53and TFAM IHC pixelwise H-scores. ROC analysis yielded a TFAM IHC pixelwise H-score cutoff of 43.0 (AUC = 0.650, 95%CI = 0.515–0.785, p = 0.047; sensitivity = 0.490, specificity = 0.810) to dichotomize high and low groups. In multi-variate Cox regression, low TFAM IHC pixelwise H-score (HR = 2.332, 95%CI = 1.136–4.787, p = 0.021), M1 status (HR = 3.582, 95%CI = 1.608–7.979, p = 0.002), and perineural invasion (HR = 4.506, 95%CI = 1.541–13.177, p = 0.006) were identified as independent variables to poor prognosis with elevated HRs. Among patients with high TFAM expression, higher HER2 IHC pixelwise H-score was associated with elevated hazard (HR = 1.010, 95%CI = 1.002–1.019, p = 0.020, Cox regression, uni-variate). Among M1 patients, higher p53 IHC pixelwise H-score was related to elevated hazard (HR = 1.029, 95%CI = 1.004–1.056, p = 0.025, Cox regression, uni-variate).ConclusionsROC and multi-variate Cox regression identified low TFAM expression as an independent poor prognostic variable for operable GAC patients, implying its potential as a quantitative prognostic biomarker. The observed associations with p53 and HER2 are hypothesis-generating and they require further validation to clarify TFAM’s role in Warburg effect and GAC progression.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12957-025-03998-6.