Chemotherapy For Advanced Gastric Cancer Research Articles

Significance of Lymph Node Metastasis in the Treatment of Gastric Cancer and Current Challenges in Determining the Extent of Metastasis.

The stomach exhibits abundant lymphatic flow, and metastasis to lymph nodes is common. In the case of gastric cancer, there is a regularity to the spread of lymph node metastasis, and it does not easily metastasize outside the regional nodes. Furthermore, when its extent is limited, nodal metastasis of gastric cancer can be cured by appropriate lymph node dissection. Therefore, identifying and determining the extent of lymph node metastasis is important for ensuring accurate diagnosis and appropriate surgical treatment in patients with gastric cancer. However, precise detection of lymph node metastasis remains difficult. Most nodal metastases in gastric cancer are microscopic metastases, which often occur in small-sized lymph nodes, and are thus difficult to diagnose both preoperatively and intraoperatively. Preoperative nodal diagnoses are mainly made using computed tomography, although the specificity of this method is low because it is mainly based on the size of the lymph node. Furthermore, peripheral nodal metastases cannot be palpated intraoperatively, nodal harvesting of resected specimens remains difficult, and the number of lymph nodes detected vary greatly depending on the skill of the technician. Based on these findings, gastrectomy with prophylactic lymph node dissection is considered the standard surgical procedure for gastric cancer. In contrast, several groups have examined the value of sentinel node biopsy for accurately evaluating nodal metastasis in patients with early gastric cancer, reporting high sensitivity and accuracy. Sentinel node biopsy is also important for individualizing and optimizing the extent of uniform prophylactic lymph node dissection and determining whether patients are indicated for function-preserving curative gastrectomy, which is superior in preventing post-gastrectomy symptoms and maintaining dietary habits. Notably, advancements in surgical treatment for early gastric cancer are expected to result in individualized surgical strategies with sentinel node biopsy. Chemotherapy for advanced gastric cancer has also progressed, and conversion gastrectomy can now be performed after downstaging, even in cases previously regarded as inoperable. In this review, we discuss the importance of determining lymph node metastasis in the treatment of gastric cancer, the associated difficulties, and the need to investigate strategies that can improve the diagnosis of lymph node metastasis.

Early Tumor-Immune Microenvironmental Remodeling and Response to First-Line Fluoropyrimidine and Platinum Chemotherapy in Advanced Gastric Cancer.

Using paired pretreatment and on-treatment samples during standard first-line chemotherapy, we identify chemotherapy-induced NK-cell infiltration, macrophage repolarization, and increased antigen presentation among responders. Increased LAG3 expression and decreased dendritic cell abundance were seen in nonresponders, emphasizing remodeling of the TME during chemotherapy response and resistance. This article is highlighted in the In This Issue feature, p. 873.

Prognostic factors to predict the survival in patients with advanced gastric cancer who receive later-line nivolumab monotherapy-The Asahikawa Gastric Cancer Cohort Study (AGCC).

BackgroundChemotherapy for advanced gastric cancer is recommended in the guidelines; however, later‐line treatment remains controversial. Since immune checkpoint inhibitors have been used for the treatment of various malignancies, trials have been performed for gastric cancer. A phase 3 trial indicated the survival benefit of nivolumab monotherapy for gastric cancer patients treated with prior chemotherapy regimens.Patients and methodsA regional cohort study was undertaken to determine the real‐world data of nivolumab treatment for patients with advanced or recurrent gastric cancer. The patients were enrolled for 2 years from October 2017 to October 2019 and were prospectively followed for 1 year to examine the overall survival (OS). The patient characteristics were analyzed in a multivariate analysis and a nomogram to predict the probability of survival was generated.ResultsIn total, 70 patients who received nivolumab as ≥third‐line chemotherapy were included in the Asahikawa Gastric Cancer Cohort. The median OS was 7.5 (95% CI, 4.8–10.2) months and the response rate was 18.6%. Diffuse type classification, bone metastasis, high neutrophil/lymphocyte ratio, and high CRP were associated with poor OS/prognosis in the multivariate analysis. A nomogram was developed based on these clinical parameters and the concordance index was 0.80 (95% CI, 0.68–0.91). The responders were aged and were frequently diagnosed with intestinal type gastric cancer, including patients with a HER2‐positive status (27.3%) or microsatellite instability‐high (27.3%) status.ConclusionsThe regional cohort study of nivolumab monotherapy for gastric cancer patients revealed prognostic factors and a nomogram was developed that could predict the probability of survival.

Segmentation of Gastric Computerized Tomography Images under Intelligent Algorithms in Evaluation of Efficacy of Decitabine Combined with Paclitaxel in Treatment of Gastric Cancer.

To analyze the evaluation of artificial intelligence algorithm combined with gastric computed tomography (CT) image in clinical chemotherapy for advanced gastric cancer, 112 patients with advanced gastric cancer were selected as the research object. Among which, 56 patients in the experimental group received paclitaxel (PTX) combined with decitabine sequential decitabine maintenance therapy. Fifty-six patients in the control group received first-line treatment with decitabine combined with cisplatin. The image segmentation algorithm based on fast interactive dictionary selection was used to process gastric CT images. Complete response (CR), partial response (PR), stable disease (SD), progressive disease (PD), response rate (RR), disease control rate (DCR), and overall survival (OS) after treatment were recorded. The true-positive rate (TPR) and coincidence ratio (CR) of the proposed algorithm for image segmentation were significantly higher than those of the mean shift algorithm and the iCoseg algorithm. The mean edge distance (MED) and edge distance variance (EDV) were significantly lower than the mean shift algorithm and the iCoseg algorithm, and the differences were considerable (P < 0.05). The number of CR (5 cases), PR (13 cases), RR (18 cases), and DCR (44 cases) in the experimental group was significantly higher than that in the control group, while the number of PD (12 cases) was significantly lower than that in the control group (P < 0.05). The number of patients complicated with hematological toxicity, leucopenia, thrombocytopenia, and digestive tract reaction in the experimental group was less than that in the control group (P < 0.05). From the comparison of long-term efficacy, the survival rate of patients in both groups showed a decreasing trend within 24 months, but the decreasing trend of survival rate of patients in the experimental group was better than that in the control group. In short, the proposed algorithm had better segmentation performance than traditional algorithms. Compared with first-line treatment with decitabine and cisplatin, PTX in combination with decitabine sequential citabine maintenance regimens had better disease control rates, lower toxicity, and more effective improvements in patient quality of life and longer survival in patients with advanced gastric cancer.

Advances in the controversies of neoadjuvant chemotherapy for advanced gastric cancer

Advances in the controversies of neoadjuvant chemotherapy for advanced gastric cancer

Predicting Response to Systemic Chemotherapy for Advanced Gastric Cancer Using Pre-Treatment Dual-Energy CT Radiomics: A Pilot Study.

ObjectiveTo build and assess a pre-treatment dual-energy CT-based clinical-radiomics nomogram for the individualized prediction of clinical response to systemic chemotherapy in advanced gastric cancer (AGC).MethodsA total of 69 pathologically confirmed AGC patients who underwent dual-energy CT before systemic chemotherapy were enrolled from two centers in this retrospective study. Treatment response was determined with follow-up CT according to the RECIST standard. Quantitative radiomics metrics of the primary lesion were extracted from three sets of monochromatic images (40, 70, and 100 keV) at venous phase. Univariate analysis and least absolute shrinkage and selection operator (LASSO) were used to select the most relevant radiomics features. Multivariable logistic regression was performed to establish a clinical model, three monochromatic radiomics models, and a combined multi-energy model. ROC analysis and DeLong test were used to evaluate and compare the predictive performance among models. A clinical-radiomics nomogram was developed; moreover, its discrimination, calibration, and clinical usefulness were assessed.ResultAmong the included patients, 24 responded to the systemic chemotherapy. Clinical stage and the iodine concentration (IC) of the tumor were significant clinical predictors of chemotherapy response (all p < 0.05). The multi-energy radiomics model showed a higher predictive capability (AUC = 0.914) than two monochromatic radiomics models and the clinical model (AUC: 40 keV = 0.747, 70 keV = 0.793, clinical = 0.775); however, the predictive accuracy of the 100-keV model (AUC: 0.881) was not statistically different (p = 0.221). The clinical-radiomics nomogram integrating the multi-energy radiomics signature with IC value and clinical stage showed good calibration and discrimination with an AUC of 0.934. Decision curve analysis proved the clinical usefulness of the nomogram and multi-energy radiomics model.ConclusionThe pre-treatment DECT-based clinical-radiomics nomogram showed good performance in predicting clinical response to systemic chemotherapy in AGC, which may contribute to clinical decision-making and improving patient survival.

1413P Antibiotic administration and outcome of patients with advanced gastric cancer receiving programmed death-1 inhibitors or with single-agent chemotherapy

Antibiotic therapy disrupts microbiota homeostasis, which is suggested to impair response to immune checkpoint blockade. We assessed whether antibiotic treatment predicts treatment outcomes of programmed death-1 (PD-1) inhibitors or chemotherapy in advanced gastric cancer (AGC).

1417P Prediction of the peritoneal recurrence by macroscopic diagnosis of the serosal invasion in gastric cancer: Supplementary analysis of JCOG0110 study

The indication for postoperative adjuvant chemotherapy for advanced gastric cancer is determined based on the pathological diagnosis. However, several investigators have reported that serosal invasion diagnosed macroscopically during surgery is superior to pathological diagnosis for the prediction of peritoneal recurrence. In order to seek more sensitive predictive factors for peritoneal recurrence, predictability of peritoneal recurrence and survival by serosal invasion diagnosed macroscopically during surgery (sT) and diagnosed pathologically (pT) were investigated.

Nivolumab plus chemotherapy for advanced gastric cancer and oesophageal adenocarcinoma.

Nivolumab plus chemotherapy for advanced gastric cancer and oesophageal adenocarcinoma.

A Machine Learning Model for Predicting a Major Response to Neoadjuvant Chemotherapy in Advanced Gastric Cancer.

AimsTo develop and validate a model for predicting major pathological response to neoadjuvant chemotherapy (NAC) in advanced gastric cancer (AGC) based on a machine learning algorithm.MethodA total of 221 patients who underwent NAC and radical gastrectomy between February 2013 and September 2020 were enrolled in this study. A total of 144 patients were assigned to the training cohort for model building, and 77 patients were assigned to the validation cohort. A major pathological response was defined as primary tumor regressing to ypT0 or T1. Radiomic features extracted from venous-phase computed tomography (CT) images were selected by machine learning algorithms to calculate a radscore. Together with other clinical variables selected by univariate analysis, the radscores were included in a binary logistic regression analysis to construct an integrated prediction model. The data obtained for the validation cohort were used to test the predictive accuracy of the model.ResultA total of 27.6% (61/221) patients achieved a major pathological response. Five features of 572 radiomic features were selected to calculate the radscores. The final established model incorporates adenocarcinoma differentiation and radscores. The model showed satisfactory predictive accuracy with a C-index of 0.763 and good fitting between the validation data and the model in the calibration curve.ConclusionA prediction model incorporating adenocarcinoma differentiation and radscores was developed and validated. The model helps stratify patients according to their potential sensitivity to NAC and could serve as an individualized treatment strategy-making tool for AGC patients.

Optimizing the program of sequential chemotherapy for advanced gastric cancer based on gene-level CNVs called from ctDNA.

e16068 Background: Tumor evolutionary trade-offs under treatment pressure can be utilized to optimize therapy. We aimed to profile the dynamic pattern of gene-level copy number variations (CNVs) for advance gastric cancer (GCA) patients who underwent sequential chemotherapy and optimized the therapy program. Methods: 27 chemo-naive advanced GCA patients with distant metastasis were enrolled. Peripheral blood samples were collected at different time points, including pre-therapy and disease progression on a specific regimen. Gene-level CNVs were called from ctDNA of blood samples and drug modified score (DMS) was defined as the ratio of CNV value between samples of pre- and post-treatment for each gene. Positive and negative DMS of a gene represented its resistance and sensitivity to a selected regimen, respectively. Then, the best initial regimen was selected and the optimal program of sequential chemotherapy was designed for each patient. Results: DMS of gene was calculated for four chemotherapy regimens, including platinum-based doublet regimen (Pt-2d), oral-fluorouracil prodrug (O-FP), paclitaxel-based regimen (PTX) and irinotecan-based regimen (CPT-11). Based on DMS distribution, resistant and sensitive genes were determined for each regimen through a heuristic method. Functional enrichment analysis showed that resistant genes mainly involved in cellular response to oxygen-containing compound and regulation of cell proliferation, while sensitive genes mainly involved in positive regulation of macromolecule biosynthetic process and regulation of apoptotic process. Then, drug resistant score (DRS, defined as DMS weighted sum of CNV values of resistant genes) was calculated and the regimen with the lowest DRS was selected as the best initial treatment for each patient. The best initial treatment of 16 patients was CPT-11, of 8 patients was O-FP, of 2 patients was Pt-2d and of 1 patient was PTX. Following that, the optimal program of sequential chemotherapy was designed according to the percentage of shared resistant genes between regimens for each patient, where two regimens with the lowest percentage were recommended to use one by one. Finally, prognostic analysis showed that differences between the optimal and practical program of sequential chemotherapy were negatively correlated to overall survival of patients. Conclusions: Based on gene-level CNVs called from ctDNA of blood samples, we determined the best initial treatment and designed the optimal program of sequential chemotherapy for advanced GCA patients, pacing a key step toward precision medicine in GCA field.

Advanced gastric cancer: CT radiomics prediction and early detection of downstaging with neoadjuvant chemotherapy

ObjectivesTo develop and evaluate machine learning models using baseline and restaging computed tomography (CT) for predicting and early detecting pathological downstaging (pDS) with neoadjuvant chemotherapy in advanced gastric cancer (AGC).MethodsWe collected 292 AGC patients who received neoadjuvant chemotherapy. They were classified into (a) primary cohort (206 patients with 3–4 cycles chemotherapy) for model development and internal validation, (b) testing cohort I (46 patients with 3–4 cycles chemotherapy) for evaluating models’ predictive ability before and after the complete course, and (c) testing cohort II (n = 40) for model evaluation on its performance at early treatment. We extracted 1,231 radiomics features from venous phase CT at baseline and restaging. We selected radiomics models based on 28 cross-combination models and measured the areas under the curve (AUC). Our prediction radiomics (PR) model is designed to predict pDS outcomes using baseline CT. Detection radiomics (DR) model is applied to restaging CT for early pDS detection.ResultsPR model achieved promising outcomes in two testing cohorts (AUC 0.750, p = .009 and AUC 0.889, p = .000). DR model also showed a good predictive ability (AUC 0.922, p = .000 and AUC 0.850, p = .000), outperforming the commonly used RECIST method (NRI 39.5% and NRI 35.4%). Furthermore, the improved DR model with averaging outcome scores of PR and DR models showed boosted results in two testing cohorts (AUC 0.961, p = .000 and AUC 0.921, p = .000).ConclusionsCT-based radiomics models perform well on prediction and early detection tasks of pDS and can potentially assist surgical decision-making in AGC patients.Key Points• Baseline contrast-enhanced computed tomography (CECT)-based radiomics features were predictive of pathological downstaging, allowing accurate identification of non-responders before therapy.• Restaging CECT-based radiomics features were predictive to achieve pDS after and even at an early stage of neoadjuvant chemotherapy.• Combination of baseline and restaging CECT-based radiomics features was promising for early detection and preoperative evaluation of pathological downstaging of AGC.

Maintenance in gastric cancer: New life for an old issue?

The interest in maintenance therapy for patients with advanced cancers has been rapidly growing. Maintenance therapy is a useful strategy that may strengthen results of induction therapy thus extending survival and preserving the quality of life (QoL) with less toxicity. Maintenance also represents a suitable setting to investigate novel agents. The value of maintenance therapy after first-line chemotherapy has been well established in several solid tumours, such as colorectal, lung, breast, and ovarian cancer in which it is largely adopted. To date, there is no established role for maintenance therapy following first-line chemotherapy for advanced gastric cancer (GC). This review summarizes the current knowledge regarding maintenance strategies in advanced GC exploring cytotoxic agents, biologic agents and immunotherapy. We also critically review new issues to optimize randomized clinical trials for maintenance therapies and suggest clinical consideration to guide a personalized approach in daily clinical practice for this setting.

Cholinesterase is Associated With Prognosis and Response to Chemotherapy in Advanced Gastric Cancer.

Background: Cholinesterase (CHE) is a routine serum biomarker in gastric cancer (GC). However, little research has been done on its clinical value in advanced GC. In addition, it is not clear whether it can be used as biomarker for the response and prognosis of advanced GC patients. Methods: Between Jan. 2013 and Dec. 2016, a total of 150 patients with advanced GC treated with first-line chemotherapy were admitted to Changzhou Tumor Hospital Affiliated to Soochow University. We retrospectively identified serum CHE level on the day before chemotherapy and at the end of chemotherapy and abstracted clinicopathologic features and treatment outcomes. Univariate and multivariate survival analyses were performed to assess the relationship between serum CHE levels and progression-free survival (PFS) and overall survival (OS). Results: A total of 150 advanced GC patients were included and divided into serum level ≥5,000 IU/L and serum level <5,000 IU/L. CHE level lower than 5,000 IU/L was associated with poorer PFS (HR, 1.60; 95% CI, 1.141–2.243; p = 0.006), poorer OS (HR, 1.76; 95% CI, 1.228–2.515; p = 0.002) and trend of poorer response (HR, 0.56; 95% CI, 0.272–1.129; p = 0.104). In univariate and multivariate logistic regression analysis, only liver metastasis and PS score were significantly associated with objective response (p < 0.05). The medium PFS was 8.0 months in patients with post-treatment CHE increased vs. 3.8 months in patients with CHE decreased after chemotherapy (HR, 1.82; 95% CI 1.28–2.57; p = 0.0002). The medium OS was 13.1 months in patients with increased post-treatment CHE vs. 8.1 months in patients with decreased post-treatment CHE (HR, 1.87; 95% CI 1.29–2.71; p = 0.0002). Conclusion: Advanced GC with CHE levels below 5,000 IU/L was significantly associated with poor PFS and OS. The results suggested that CHE analysis before chemotherapy was a promising prognostic marker for advanced GC.

Psoas muscle depletion during preoperative chemotherapy for advanced gastric cancer has a negative impact on long-term outcomes after gastrectomy.

AimThe significance of sarcopenia in cancers has been widely recognized. However, few studies have focused on chronological changes in sarcopenia in cancer patients. This study aimed to clarify the clinical significance of changes in the psoas muscle area before and after preoperative chemotherapy.MethodsThis study included 39 patients who underwent gastrectomy followed by preoperative chemotherapy for advanced gastric cancer between January 2010 and December 2016 in our hospital. The psoas muscle area was measured at the umbilical level before and after chemotherapy, and the relationship between its chronological changes and the long‐term prognosis was examined.ResultsPatients were classified into two groups according to changes in the psoas muscle area before and after preoperative chemotherapy: remarkable muscle depletion and normal groups. No significant differences were observed in clinicopathological factors. Notably, the remarkable muscle depletion group included significantly more male patients (P = .018) and showed a high weight loss rate (P < .001). Although no significant difference was observed in the recurrence‐free survival between the two groups (P = .484), overall survival was significantly worse in the remarkable muscle depletion group (P < .001). Multivariate analysis for prognosis revealed that pathological stage III or higher (P = .022) and decreased psoas muscle area (P = .038) were independent prognostic factors.ConclusionsThe present findings suggest that psoas muscle depletion during preoperative chemotherapy is a prognostic factor for poor long‐term outcomes in patients who underwent gastrectomy followed by preoperative chemotherapy for advanced gastric cancer.

Intraperitoneal paclitaxel and systemic chemotherapy for advanced gastric cancer with synchronous peritoneal metastasis

Intraperitoneal paclitaxel and systemic chemotherapy for advanced gastric cancer with synchronous peritoneal metastasis

Effect of early tumor response on the health-related quality of life among patients on second-line chemotherapy for advanced gastric cancer in the ABSOLUTE trial

BackgroundThis study evaluated the association between early tumor response at 8 weeks, previously reported as a positive outcome prognosticator, and health-related quality of life (HRQOL) in advanced gastric cancer (AGC) patients enrolled in the ABSOLUTE trial.MethodsHRQOL was assessed using the EuroQol-5 Dimension (EQ-5D) utility index score in patients with complete response (CR) + partial response (PR) and progressive disease (PD) at 8 weeks, and time-to-deterioration (TtD) of the EQ-5D score, with the preset minimally important difference (MID) of 0.05, was compared between these populations. Among the enrolled patients, 143 and 160 patients were assessable in weekly solvent-based paclitaxel (Sb-PTX) arm and weekly nanoparticle albumin-bound paclitaxel (nab-PTX) arm, respectively.ResultsChanges of the EQ-5D score from baseline to 8 weeks in the nab-PTX arm were 0.0009 and − 0.1229 in CR + PR and PD patients, respectively; the corresponding values for the Sb-PTX arm were − 0.0019 and − 0.1549. For both treatments, changes of the EQ-5D score from baseline at 8 weeks were significantly larger in patients with PD than in those with CR + PR. The median TtD was 3.9 and 2.2 months in patients with CR + PR and PD, respectively, for nab-PTX [hazard ratio (HR) = 0.595, 95% confidence interval (CI) 0.358–0.989]. For Sb-PTX, the corresponding values were 4.7 and 2.0 months (HR = 0.494, 95% CI 0.291–0.841).ConclusionsEarly tumor shrinkage was associated with maintained HRQOL in AGC patients on the second-line chemotherapy with taxanes.

Efficacy of the Preoperative Albumin-Bilirubin Grade for Predicting Survival and Outcomes of Postoperative Chemotherapy for Advanced Gastric Cancer.

PurposeThe liver function index can predict the prognosis of hepatocellular carcinoma and many other non-neoplastic diseases. We aimed to determine whether the preoperative albumin–bilirubin (ALBI) grade could predict the prognosis of patients with gastric cancer (GC).Patients and MethodsData of 243 patients with GC who underwent radical resection were collected retrospectively. Patients were divided into the high ALBI (>−2.34) and low ALBI (≤−2.34) grade groups. Overall survival was analyzed between the two groups using the Kaplan–Meier curves. Univariate and multivariate analyses identified the independent factors associated with postoperative complications and overall survival.ResultsThe postoperative complication rates were higher in the high ALBI grade group than in the low ALBI grade group (P=0.005). The high ALBI grade group also had worse overall survival (P<0.001), especially TNM stage II–III patients (stage II, P=0.043; stage III, P<0.001). In the high ALBI grade group, patients with TNM stage III not undergoing chemotherapy had significantly worse survival times (P=0.001). High ALBI grade (P=0.032), Charlson score of 1–2 (P=0.007), and laparotomy surgery (P=0.045) were independent risk factors for postoperative complications. High ALBI grade (P=0.005), age ≥70 years (P=0.002), nutritional risk screening score 2002 score of 5–6 (P=0.019), tumor located in the cardia (P=0.020), diffuse tumor (P<0.001), and TNM stage III (P<0.001) were independent risk factors for overall survival.ConclusionPreoperative ALBI grade could predict postoperative complications and overall survival of patients with GC, especially those with TNM stages II–III. This grading method has the advantages of preoperative availability, simplicity, and objectivity and aids in improving preoperative prognosis prediction and in achieving better outcomes of postoperative chemotherapy.

Loss of skeletal muscle mass during palliative chemotherapy is a poor prognostic factor in patients with advanced gastric cancer

Cancer causes muscle mass loss, which is associated with a poor prognosis. Chemotherapy may also reduce muscle mass. We investigated skeletal muscle mass change during palliative chemotherapy for advanced gastric cancer (AGC) and its association with treatment outcomes. We retrospectively reviewed 111 consecutive AGC patients who underwent first-line palliative chemotherapy. Skeletal muscle area was measured before and after chemotherapy at the third lumbar vertebra level using computed tomography scans. We compared skeletal muscle index (SMI), body mass index (BMI), and body weight changes to chemotherapy response and survival. The 80 male and 31 female patients’ median age was 65 (range 31–87) years, and 46.8% had sarcopenia at baseline. Median pre-chemotherapy to post-chemotherapy SMI, BMI, and body weight decreases were − 4.5 cm2/m2 (− 11.3%) (P < 0.001); − 0.7 kg/m2 (− 3.2%) (P < 0.001); and − 2.0 kg (− 3.5%) (P < 0.001), respectively. Median SMI decreases for patients with objective response, stable disease, and disease progression were − 4.0 cm2/m2 (range − 20.1 ~ 9.5); − 4.5 cm2/m2 (range − 19.8 ~ 0.8); and − 3.8 cm2/m2 (range: − 17.6 ~ 0.1), respectively. Response to chemotherapy was not associated with SMI decrease (P = 0.463). In multivariable analysis, sarcopenia at baseline (HR 1.681; 95% CI 1.083–2.609, P = 0.021), decreased SMI (HR 1.620; 95% CI 1.041–2.520; P = 0.032) were significant poor prognostic factors for survival. Skeletal muscle mass decreased significantly during chemotherapy in AGC patients, but was not associated with chemotherapy response. Decreased SMI was a poor prognostic factor in AGC patients during first-line palliative chemotherapy.

Prognostic Value of Serum Soluble Programmed Death-Ligand 1 and Dynamics During Chemotherapy in Advanced Gastric Cancer Patients.

PurposeThe soluble form programmed death-ligand 1 (sPDL1) has immunosuppressive properties and is being studied as a candidate biomarker for immuno-oncology drug development. We measured the serum sPDL1 at pre-and post-chemotherapy and evaluated its prognostic implication and dynamics during chemotherapy in advanced gastric cancer (GC).Materials and MethodsWe prospectively enrolled 68 GC patients who were candidates for palliative standard first-line chemotherapy, and serially collected blood at baseline and after one cycle of chemotherapy, at the best response and after disease progression. sPDL1 was measured using an enzyme-linked immunosorbent assay. Response to chemotherapy, overall survival (OS), progression-free survival (PFS) and other prognostic factors including neutrophil-lymphocyte ratio (NLR) were obtained. The cut-off value of sPDL1 levels for survival analysis was found using C-statistics.ResultsThe median baseline sPDL1 was 0.8 ng/mL (range, 0.06 to 6.06 ng/mL). The median OS and PFS were 14.9 months and 8.0 months, respectively. sPDL1 and NLR showed a weak positive correlation (Spearman’s rho=0.301, p=0.013). Patients with low levels of sPDL1 at diagnosis (< 1.92 ng/mL) showed a better OS and PFS than patients with a high sPDL1. The baseline sPDL1 before treatment was higher in the progressive disease group than in the stable disease and partial response groups. Patients whose sPDL1 increased after the first cycle of chemotherapy showed worse PFS and OS. Following disease progression, sPDL1 increased compared with the baseline.ConclusionsPDL1 at prechemotherapy confers a prognostic value for PFS and OS in GC patients under palliative first-line chemotherapy. Dynamics of sPDL1 during chemotherapy correlates with disease progression.