• FLOT
• gastric cancer
• immune profiling
• nanostring
• perioperative

Background. Gastric cancer (GC) represents the fifth most frequently diagnosed tumour and the third leading cause of cancer-related death worldwide. In the last decades, a compelling body of evidence has progressively provided new insights into the definition of new epidemiological, clinical, pathologic and molecular features, new emerging biomarkers and different treatment options in all settings of GC disease.
In the setting of locally advanced resectable GC/ gastroesophageal junction carcinoma (GEJC), perioperative FLOT (fluorouracil, oxaliplatin, docetaxel) recently became the new standard of care, revealing a significant improvement in survival. Moreover, moving from the first signals of immunotherapy potential efficacy in advanced disease and from new molecular insights, many efforts have been focused on optimising the preoperative treatment strategies, as combining immunotherapies with chemotherapies.
Taking into account the complexity and heterogeneity of GC, in order to choose the best therapeutic strategy, the best timing and the selected patient, we cannot avoid a more profound knowledge of tumour microenvironment (TME) and of its modifications. Indeed, TME is a niche of stromal, immune and tumoural cells and extracellular matrix components in which cells cross talk through a huge reciprocal exchange of molecular information, above all in GC, and it influences the tumour behaviour and the treatment response.

Aim. Accordingly, our aim is to analyse the TME of pre and post treatment samples of patients treated with perioperative FLOT and to study both its baseline characteristics and its modifications after neoadjuvant therapy, in order to unravel new potential strategies to enhance the efficacy of chemotherapy.

Materials and methods. We prospectively analysed both diagnostic biopsies (PRE) and surgical samples (POST) from patients treated with perioperative FLOT at our centre. We collected clinicopathologic data (age, gender, clinical TNM, tumour location, pathological TNM, histotype, grading, tumour regression grade) and molecular data (HER2, MSI and EBV evaluation). Using RNA extracted from TME of the paired samples, we performed gene expression profile using NanoString nCounter® PanCancer Panel, a computational advanced analysis that allows to measure the expression of 730 immune-related genes (and 40 housekeeping genes), corresponding to 14 immune cell types and 22 immune functions.

Results. We enrolled a total of 25 consecutive patients eligible for the study, 22 male and 3 female, with a median age of 63 years. Clinical T stage was cT3-4 in the majority of cases (88%) and N-positive status in all cases. According to Lauren’s histotype, 8 cases were diffuse, 7 intestinal, 2 mixed and 8 were not detailed. Three cases were HER2 positive, only 1 was MSI high and all cases were EBV negative.
After a median follow-up of 29.8 months, 9 patients (36.0%) had progressed and 6 (24.0%) had died. The estimated survival rate was 81% at 1 year and 64% at 2 years. The number of events were not enough to obtain median disease free and overall survival estimations and to provide survival correlations. T-regression, considered as the reduction from a baseline cT3-4 to an ypT0-2, was achieved in 5 patients (20%), while 4 patients (16.0%) reported an ypN0 stage (N-clearance).
At a first unsupervised hierarchical method analysis performed with Nanostring panel, all samples were considered jointly: even though analysed without any descriptors, the method recognized similarities and almost exactly distinguished PRE and POST samples, demonstrating that chemotherapy could have an impact on TME changing its immune profile.
Looking at the differential gene expressions, when POST were compared with the PRE samples, the main features of the differential expression were traced in hyper expressed genes from gene sets related to cytotoxicity, T cell functions, complement system, TNF superfamily, cell cycle and regulation.
Among post samples, the main modifications in immune gene sets resulted related to T regression covariate, which we went to look more in detail. Cases with pre-treatment activation were the ones that preferentially reported tumour regression, with a baseline activation of cytotoxicity system and T cell functions carrying higher expression of granzyme, perforin and grunulysin. After treatment, these cases remained activated and also other samples revealed FLOT-induced changes, globally showing a hyper activation of T cell functions, B cell functions, antigen processing and cytotoxicity that seemed to be involve in treatment response.
If we consider patients with consequently tumour regression compared with patients who didn’t achieve it, their pre-treatment samples showed a high percentage of all immune cells, exception made for neutrophils; similarly, their post-treatment samples presented a markedly higher percentage of B cells, T cells, NK cells, CD8+ T cells, while neutrophils and above all mast cells appeared to be reduced.

Conclusions. Our analysis suggested that FLOT regimen could have an impact on immune TME of GC/GEJC patients and may help to convert immune “cold” cancers to immune “hot” ones. The presence of activated cytotoxic T cells with granulysin, perforin, granzymes expression were important for achieving treatment response with chemotherapy, either if already presented at baseline or if induced by chemotherapy.
The upregulation of B cells, T cell, CD8+ T cells were associated with better response to chemotherapy, together with a downregulation of mast cells and neutrophils.
Further analyses and longer follow up were ongoing, in order These findings needed to be were consistent with the anti-tumour immunity role of T cells and CD8+ T cells and with the pro-angiogenic and pro-tumorigenic role of mast cells, as well as their relationship with neutrophils.
This immune phenotype could be exploited to potentiate a treatment response or probably to gain efficacy in non-responders, also in chemo-immunotherapy combinations in which FLOT could be a valid chemotherapy backbone.
Considering the small samples size, the preliminary results and the relevance of the issue, additional evaluations should be integrated in order to put our data in context and further analyses are still needed.