Neoplasms

All Conditions

Digestive System Diseases

Rare Diseases

Carcinoma

Sarcoma

Colorectal Neoplasms

Neoplasms by Histologic Type

Neoplasms, Connective and Soft Tissue

Intestinal Neoplasms

Gastrointestinal Neoplasms

Digestive System Neoplasms

Gastrointestinal Diseases

Colonic Diseases

Intestinal Diseases

Rectal Diseases

Soft Tissue Sarcoma

Patients with advanced/metastatic soft-tissue sarcoma

Patients with metastatic colorectal carcinoma

Tumor and blood samples will be sequenced at medium-high coverage at the whole genome (exome) and transcriptome levels (RNA Seq). This will allow detecting variants in a larger set of samples even though only from the main clone will be precisely measured. The whole exome will be performed at a mean coverage of at least 60x for the normal DNA samples and 120x for the tumor DNA samples. The transcriptome of the tumor will be performed at enough depth of coverage to detect gene fusions, transcriptome variants and measure the digital expression of already annotated isoforms.

For both sequencing configurations:

* Data from each cancer and normal genome will be analysed for the presence of somatic variants.
* DNA and RNA sequencing results will be integrated.
* Technical replication for the mutations / chromosome alterations / transcript fusions that most likely drive the tumour process will be performed via Target Resequencing of the genomic / coding regions of interest.

Next Generation Sequencing (NGS): exome, RNA seq

Next Generation Sequencing in cancer: a feasibility study in France to assess sample circuit and to perform analyzes within a limited time.

The first France disease genomic medicine program in the field of cancer has been retained by the 2025 Genomic Medicine France Plan. This program, called MULTIPLI encompasses two innovative personalized medicine clinical trials in soft-tissue sarcoma and colorectal carcinoma involving targeted molecules according to the tumor profile of each patient.

This 1st clinical research program aims implementing exome sequencing and RNA sequencing to determine the genomic profile and to provide a therapeutic decision for each patient. Genomic analyzes will be performed on different technical platforms: samples will be collected in each investigating center, nucleic acids extraction will be performed on two genetic platforms, Inca labeled and identified for the purpose of this study: Institut Bergonié and Hôpital Européen Georges Pompidou. CNRGH (Centre National de Recherche en Génomique Humaine) was retained for operational platform genomics and Institut Bergonie for bioinformatics data processing. Each genomic profile will be discussed within a multidisciplinary tumor board which aims at providing a therapeutic decision for each patient and to propose a targeted treatment in case of actionable molecular alteration.

The purpose of this program is to perform analysis on a set of gene, in order to provide results no more than after 6 weeks after the sample arrival on the biopathological platform. This gene panel analysis is based on the predefined list of genes that are direct targets of the drugs available in the MULTIPLI program.

Before implanting this program in a large-scale launch, it was essential to set up a pilot study in order to evaluate both sample's management between several platforms, and the time to report the results, and to verify that it was in line with the objectives set.

For each participant, biological specimens will be collected for molecular analysis :

* Whole blood sample for constitutional characteristics
* Tumor sample (fresh-frozen or formalin-fixed paraffin embedded)

Molecular Profiling to Improve Outcome of Patients in Cancer. A Pilot Study

Molecular Profiling to Improve Outcome of Patients in Cancer. A Pilot Study (MULTIPLI-0)

The time delay between the date of sample receipt by the platform and the date of dispatch of a validated MTB report to physician

Rate of patients for whom a report was transmitted, within the patients for whom the samples were received by the platforms

The time delay between the date of informed consent signature and the date of dispatch of a validated MTB report to physician

Rate of patients for whom a report was transmitted, within the patients for whom signed consent has been signed

The time delay between the date of informed consent signature and the date of sample receipt on platform

Rate of patients for whom samples have been received by platform, within the patients for whom signed consent has been signed

The time delay between the date of sample receipt on platform and the date of nucleic acids receipt on CNRGH

Rate of patients for whom samples have been received by platform, within the patients for whom sending date has been completed on electronic case

Rate of patients for whom samples have been qualified in first step by platform and nucleic acids received by CNRGH, within the patients for whom samples have been received by platform

Rate of patients for whom samples have been qualified in second step by platform and nucleic acids received by CNRGH, within the patients for whom samples have been received by platform

Rate of patients for whom samples have been qualified in first and second step by platform and nucleic acids received by CNRGH, within the patients for whom samples have been received by platform

The time delay between the date of nucleic acids receipt on CNRGH and the date of receipt of all sequencing files by bioinformatic platform

Rate of patients for whom all sequencing files have been qualified by bioinformatics platform, within the patients for whom samples have been received by CNRGH

Rate of patients for whom sequencing have been qualified by CNRGH, within the patients for whom samples have been received by CNRGH

The time delay between the date of receipt of all sequencing files by bioinformatics platform and the date of receipt of bioinformatics analysis by biologist for interpretation

Rate of patients for whom all sequencing file have been qualified by bioinformatic platform, within the patients for whom all sequencing file have been received by bioinformatic platform

Rate of patients for whom bioinformatic analysis have been transmitted for interpretation, within the patients for whom all sequencing file have been received by bioinformatic platform

The time delay between the date of bioinformatic analysis availability for interpretation and the date of dispatch of a validated MTB report to physician

Rate of patients for whom bioinformatic analysis has been interpreted by biologist, within the patients for whom bioinformatics analysis have been transmitted

Rate of patients for whom biological report has been discussed by MTB, within the patients for whom bioinformatics analysis have been transmitted

Institut Bergonié

Plateforme labellisée Inca - Institut Bergonié, Bordeaux

Plateforme labellisée Inca - Hôpital Européen Georges Pompidou, Paris

CNRGH, Evry

EUCLID Clinical Trial Platform

Institut National de la Santé Et de la Recherche Médicale, France

Respiratory Tract (Lung and Bronchial) Diseases

Lung Neoplasms

Neoplasms, Glandular and Epithelial

The investigators will extract total protein, DNA and RNA from PSC patients.

Integrative Analysis of pulmonary sarcomatoid carcinoma (PSC)

The investigators will analyzed proteomes of paired normal lung tissues and pulmonary sarcomatoid carcinoma with or without metastasis, sequenced transcriptomes, perform whole exome sequencing, and single nucleotide polymorphism (SNP) array profiling for triplets, each comprising normal lung tissue, primary pulmonary sarcomatoid carcinoma, and its synchronous matched metastasis, as well as analyzed genomics of lung cancer characterized previously by The Cancer Genome Atlas (TCGA) to conduct integrated proteogenomic analyses.

Integrative Analysis of Pulmonary Sarcomatoid Carcinoma (PSC)

There is no plan to make individual participant data (IPD) available to other researchers.

The Affiliated Tumor Hospital of Nantong University, Nantong, Jiangsu Province, China

Anhui Medical University

Shanghai 10th People's Hospital

Professor

Cholangiocarcinoma

Biliary Tract Neoplasms

Gallbladder Neoplasms

Adenocarcinoma

Biliary Tract Diseases

Gallbladder Diseases

Bile Duct Cancer

Biliary Tract Cancer

Gallbladder Cancer

Antineoplastic Agents

All Drugs and Chemicals

Gemcitabine

Paclitaxel

Albumin-Bound Paclitaxel

Cisplatin

Tubulin Modulators

Antimitotic Agents

Antimetabolites

- gemcitabine 800mg/m2 + cisplatin 25 mg/m2 + nab-paclitaxel 100mg/m2 on day 1 and day 8, every 21 days

nab-paclitaxel plus gemcitabine-cisplatin

Hong Jae Chon, MD,PhD

Hong Jae Chon, MD, PhD

Hongjae Chon, MD,PhD

Biliary tract cancer is a rare gastrointestinal malignant neoplasm and includes intrahepatic cholangiocarcinoma, extrahepatic cholangiocarcinoma, and gall bladder cancer. Curative surgical resection offers the only chance for cure. However, most patients with BTC are diagnosed at an unresectable stage. Therefore, the survival outcomes of patients with advanced biliary tract cancer remain dismal.

The combination of gemcitabine and cisplatin has become the current standard for advanced BTCs since the landmark ABC-02 trial in 2010. However, the median overall survival of Gem/Cis chemotherapy is less than 1 year. Recently, a triplet regimen of gemcitabine, cisplatin, and nab-paclitaxel showed promising results in a single-arm phase II multicenter study.

However, biliary tract cancer is a group of heterogenous diseases by site and genetic alteration, and this diversity may lead differences in response to systemic chemotherapy.

Transcriptome analysis through RNA-sequencing has rarely been performed in advanced biliary tract cancer, and even if it has performed, only small number of patients were included. Further research on multi-omics data is needed on the necessity and clinical significance in treatment of biliary tract cancer.

Using biopsy specimen (formalin fixed paraffin embedded tissue), in-house NGS and RNA-sequencing will be performed simultaneously. Through this, investigators will discover biomarkers based on multi-omics data that predict response to systemic chemotherapy (nab-paclitaxel plus gemcitabine-cisplatin). In addition, blood sampling will be performed in parallel to conduct research on cell-free DNA and circulating tumor cell analysis related to response and progression on chemotherapy; before administration of chemotherapy, 3 months after chemotherapy, 6 months after chemotherapy, the time of disease progression (if possible), before curative resection (if possible).

Biomarker Discovery in Patients With Advanced Biliary Tract Cancer

Discovery of Molecular Biomarkers for Predicting Response Through RNA Sequencing in Patients With Advanced Biliary Tract Cancer Who Received Nab-paclitaxel Plus Gemcitabine-cisplatin

tumor samples from patients with hepatobiliary cancers (incidence of genetic alteration, association with treatment response and survival duration)

blood samples from patients with hepatobiliary cancers (incidence of genetic alteration, association with treatment response and survival duration)

Multi-omics analysis to further subtype and find therapeutic targets of biliary tract cancer

Molecular biomarker associated with overall survival, progression-free survival and objective response rate in patients who receive Gemcitabine/Cisplatin/Nab-paclitaxel chemotherapy

Dong-A Pharmaceutical

CHA University

Patients receiving target drugs with the score value above 0,1 as monotherapy or in combination

Patients receiving only non-target drugs or target drugs with the score value equal to or below 0,1 as monotherapy or in combination

Next Generation Sequencing of RNA from tumor samples, rRNA-depleted.

RNA sequencing

Analysis of RNA-seq data using the Oncobox algorithm.

Transcriptome analysis

target drug with the score above 0,1

target drug with the score equal or below 0,1

non-target drug

palliative care

Anton A Buzdin, Ph.D., D.Sc

This is a prospective trial for a computation-based efficacy prediction method for anticancer target therapies. The original computational algorithm utilizes individual transcriptome data of a cancer sample and assesses changes at the level of gene expression and intracellular signaling pathways. By applying the database of known molecular targets of anticancer target drugs it allows to rank potential efficacies of target drugs.

Original computational algorithm Oncobox was developed to determine molecular features of individual tumors. It represents the solution for a personalized selection of target anticancer therapies. The method is based on the analysis of gene expression profile of a cancer sample in comparison with the corresponding normal tissue biosamples in order to select the most effective molecular targets for their inhibition and, accordingly, to identify more effective target drugs for cancer treatment. Histological material obtained from cancer patients during surgery or core-needle biopsy as part of standard treatment will be used for the analysis. Total RNA extracted from the tumor material will be subjected to next-generation sequencing (NGS). By comparing transcriptome profile of the tumor sample with the profiles of the corresponding normal tissue samples the rate of molecular pathways activation/deactivation will be calculated, as well as the case-to-normal ratios for the individual gene products - molecular targets of drugs. Based on these data, each target drug will be assigned with a score reflecting its potential efficacy for each individual tumor treatment. A drug with the score value above 0.1 will be considered potentially effective, a drug with the score value equal to or below 0.1 - as potentially ineffective. Following Oncobox test, 130 target anticancer drugs will be rated according to their predicted effectiveness (see the list of eligible target drugs below). This information will be fully available to a patient and his/her doctor. The doctor will prescribe treatment according to his/her consideration, e.g. based on the standards of care and the patient's life indications. After the appointment of therapy, the patients will be divided naturally into the following three observation groups. The first group will be formed from patients receiving target drugs with the score value above 0,1 as monotherapy or in combination. The second group - patients receiving only non-target drugs or target drugs with the score value equal to or below 0,1 as monotherapy or in combination. Third group will be formed by patients receiving palliative care. Within this study, these three groups will be compared by response to the therapy according to the results of instrumental studies, by time to progression and by time to progression compared to the previous line of therapy (if any). Additionally, overall survival will be measured in all three groups.

Eligible target drugs:

1. Abemaciclib (LY2835219)
2. Afatinib
3. Aflibercept
4. Alectinib
5. Alemtuzumab
6. Alitretinoin
7. Anastrozole
8. Apalutamide, ARN-509
9. Arsenic trioxide
10. Atezolizumab
11. Avelumab
12. Axitinib
13. Belinostat
14. Bevacizumab
15. Bexarotene
16. Bicalutamide
17. Binimetinib (MEK162)
18. Blinatumomab
19. Bortezomib
20. Bosutinib
21. Brentuximab vedotin
22. Brigatinib
23. Cabazitaxel
24. Cabozantinib
25. Carfilzomib
26. Ceritinib (Zykadia, LDK378)
27. Cetuximab
28. Cobimetinib
29. Crizotinib
30. CYT387 (Momelotinib)
31. Dabrafenib
32. Daratumumab
33. Dasatinib
34. Degarelix
35. Denileukin diftitox (Ontac)
36. Denosumab
37. Docetaxel
38. Dovitinib
39. Durvalumab
40. Elotuzumab
41. Encorafenib
42. Enzalutamide
43. Erlotinib
44. Estramustine
45. Everolimus
46. Exemestane
47. Flavopiridol (Alvociclib)
48. Foretinib
49. Fulvestrant
50. Ganetespib (STA-9090)
51. Gefitinib
52. Goserelin
53. Homoharringtonine (Omacetaxine mepesuccinate)
54. Ibritumomab tiuxetan
55. Ibrutinib
56. Idelalisib
57. Imatinib
58. Inotuzumab ozogamicin
59. Ipilimumab
60. Ixabepilone
61. Ixazomib (MLN9708)
62. Lapatinib
63. Lenalidomide
64. Lenvatinib
65. Letrozole
66. Leuprolide
67. Lomustine
68. Masitinib
69. Medroxyprogesterone acetate (MPA)
70. Megestrol
71. Methyltestosterone
72. Midostaurin
73. Mogamulizumab
74. Moxetumomab pasudotox
75. Necitumumab
76. Nilotinib
77. Nilutamide
78. Nimotuzumab
79. Nintedanib (BIBF 1120)
80. Niraparib
81. Nivolumab (BMS-936558)
82. Obinutuzumab
83. Ofatumumab
84. Olaparib
85. Olaratumab
86. Osimertinib
87. Paclitaxel
88. Palbociclib
89. Panitumumab
90. Panobinostat
91. Pazopanib
92. Pembrolizumab
93. Perifosine
94. Pertuzumab
95. Pomalidomide
96. Ponatinib
97. Ramucirumab (Cyramza)
98. Regorafenib
99. Ribociclib
100. Rigosertib
101. Rituximab
102. Romidepsin
103. Rucaparib
104. Ruxolitinib
105. Selumetinib
106. Siltuximab
107. Sonidegib (LDE225)
108. Sorafenib
109. Sunitinib
110. Tamoxifen
111. Tecemotide (Emepepimut-S, L-BLP25)
112. Temozolomide
113. Temsirolimus
114. Thalidomide
115. Tivantinib
116. Tivozanib
117. Toremifene
118. Trametinib (Mekinst)
119. Trastuzumab
120. Trebananib
121. Vandetanib
122. Veliparib
123. Vemurafenib
124. Venetoclax
125. Vinblastine
126. Vincristine
127. Vindesine
128. Vinorelbine
129. Vismodegib
130. Vorinostat

Formalin-fixed, paraffin-embedded pathological cancer samples obtained during surgery or core needle biopsy

Identification of Molecular Biomarkers for Cancer Target Therapy Efficacy

Study Protocol, Statistical Analysis Plan (SAP), NGS data, Clinical Study Report (CSR)

Tumor response according to the results of instrumental studies

Time to progression compared to the previous therapy lane

Oncobox Ltd

Vitamed LLC

N.N. Blokhin National Medical Research Center of Oncology

Kaluga Regional Clinical Oncology Center

Multidisciplinary medical holding SM-Clinic

Oncological Clinical Dispensary No. 1 of the Moscow City Health Department

OmicsWay Corp.

Skin and Connective Tissue Diseases

Breast Neoplasms

Breast Diseases

Skin Diseases

Trastuzumab

Mitogens

Antineoplastic Agents, Immunological

Her2-positive breast cancer patients treated with Trastuzumab (monotherapy)

Her2-positive breast cancer patients treated with Trastuzumab in combination with other regimens of chemotherapy

Standard Trastuzumab treatment regimen recommended for breast cancer

Standard chemotherapy regimen recommended for breast cancer

Chemotherapy

The purpose of the study is to identify molecular markers at the level of molecular pathway activation to predict efficacy of anti-HER2 therapy with Trastuzumab.

Biopsy and/or surgical samples from Her2-positive breast cancer patients treated with Trastuzumab alone or in combinations with other regimens of chemotherapy with known clinical outcomes will be collected and subjected to mRNA sequencing. Expression profiles will be analysed using original bioinformatic platform Oncobox. Based on comparison of molecular pathways activation strength and clinical response to Trastuzumab and chemotherapy, this study aims to identify molecular markers predicting efficacy of therapy with Trastuzumab and the possibility of further relapse.

Formalin-fixed, paraffin embedded pathological samples of breast cancer obtained during radical mastectomy or core needle biopsy

Molecular Pathway Activation Markers Predicting Efficacy of Trastuzumab Therapy for HER2-positive Breast Cancer

Study Protocol Statistical Analysis Plan (SAP) NGS data Clinical Study Report (CSR)

Tumor response by RECIST v1.1 or pathological response according to Chevallier system

Oncobox Ltd., Russia

Vitamed LLC, Russia

Republican Oncological Dispensary of Karelia Republic, Russia

Chief Scientific Officer

Stomach Neoplasms

Stomach Diseases

Stomach Cancer

After initial chemotherapy, responder (complete remission, partial remission)

After initial chemotherapy, disease progression

complete cure and no recurrence at least 1 year after treatment

non-complete cure or recurrence within 1 year after treatment

Institutinal standard chemotherapy as first line

: XP (xeloda + cisplantin) or Xelox (xeloda+oxaliplitan) +/- Herceptin

Su Youn Nam, MD, PhD

Su Youn Y Nam, MD, PhD

* discovery and validation of biomarker predicting gastric cancer chemotherapy response

  * Analysis for expression level of mRNA using Next generation sequencing in gastric cancer tissue by chemotherapy response
  * Analysis for expression level of miRNA using Next generation sequencing in gastric cancer tissue and blood by chemotherapy response
  * Validation of mRNA and miRNA using qRT-PCR in multiple independent cohort
* Biological biomarkers-clinical factor combined prediction model of gastric cancer chemotherapy response

* discovery and validation of biomarker predicting gastric cancer chemotherapy response

  * Analysis for expression level of mRNA in fresh frozen gastric cancer tissue by chemotherapy response (A) method of mRNA expression measurement: RNA sequencing (B) study group Palliative chemotherapy (inoperable patients)

    * institutional primary Chemotherapy regimen (XP or Xelox)

      1. response group
      2. progression group

         Post-OP adjuvant chemotherapy
    * institutional primary Chemotherapy regimen

      1. complete response group
      2. non-responder group

      

      1. and 2) groups: age, sex, regimen matched
  * Analysis for expression level of miRNA using Next generation sequencing in gastric cancer tissue and blood by chemotherapy response (A) method of mRNA expression measurement: RNA sequencing (B) study group

    * the same patients in mRNA sequencing
  * Validation of mRNA and miRNA in multiple independent cohort method of measurement of RNA expression: qRT-PCR
* Biological biomarkers-clinical factor combined prediction model of gastric cancer chemotherapy response combination of biologic biomarker and clinical factors to predict the chemotherapy response in gastric cancer

RNA from gastric tissue and blood

DNA from blood

Predicting Biomarker of Gastric Cancer Chemotherapy Response

Postgenome-based Systemic Discovery of Strong Biomarkers Predict Gastric Cancer Chemotherapy Response

Discovery of predicting bio-markers for gastric cancer chemotherapy response using next generation sequencing and qRT-PCR

Combination prediction model of biologic biomarkers and clinical factors for the response of adjuvant chemotherapy in gastric cancer

Combination prediction model of biologic biomarkers and clinical factors for the response of palliative chemotherapy in gastric cancer

Kyungpook National University Hospital

Carcinoma, Transitional Cell

Transitional Cell Carcinoma

Transitional Cell Cancer of the Renal Pelvis and Ureter

Nivolumab

Immune Checkpoint Inhibitors

Nivolumab 360mg intravenous adminstration every 3 weeks

If you meet all the conditions to participate in the trial, you will receive the following treatments: Your physician will give you 360 mg of Nivolumab as an intravenous infusion every 3 weeks for about 30 minutes. For safety reasons, we recommend that you stay in the hospital for 60 minutes after the initial infusion of nivolumab. There will be a total of 3 cycles of Nivolumab treatments during the study period. You will need to return every 3 weeks. Each return will collect about 50 ml (10 tsp) of blood samples, depending on local standards.

Nivolumab 100 MG in 10 ML Injection

Yu-Li Su, MD

Chien-Ya Lin, RPN

The aim of this study is to explore efficacy and safety of neoadjuvant nivolumab for non-metastatic upper tract urothelial carcinoma (UTUC), and explore the potential predictive biomarkers of immunotherapy.

Upper urinary tract urothelial carcinoma (UTUC) is a malignant tumor originated from the epithelium of upper urinary tract (renal pelvis and ureter). The standard treatment of UTUC is radical nephroureterectomy with ipsilateral bladder cuff excision. For locally advanced disease, neoadjuvant chemotherapy or adjuvant chemotherapy with radiotherapy is also a considerable treatment. In general, patients with UTUC are often diagnosed in a late stage with a poor survival.

Nowadays, immune checkpoint inhibitor (ICI) emerged huge success in treatment of various type of cancers, including metastatic urothelial carcinoma. Several anti-PD1 or PD-L1 agents demonstrated an exciting response for metastatic urothelial carcinoma. The encouraging success makes clinical trials moving forward to neoadjuvant setting. In the PURE-01 study, patients with muscle-invasive bladder cancer received 3 cycles of neoadjuvant pembrolizumab achieving 39.5% pathological complete response (pCR). It brought a brand-new hope for organ-preservation treatment strategy. So far, neoadjuvant ICI has not been tested in patients with UTUC, irrespective for treatment efficacy or safety analysis. More importantly, there is still lack of reliable biomarkers to predict treatment response of ICI, which definitely an unmet medical need in clinical practice.

Therefore, the investigators proposed a phase II, open-label study of neoadjuvant nivolumab in locally advanced UTUC. Investigators believe that neoadjuvant nivolumab will achieve at least similar pCR rate compared with neoadjuvant pembrolizumab in UCB patients. Furthermore, investigators will conduct a comprehensive exploratory genomic analysis to identify the potential candidate biomarkers to predict the response of nivolumab.

Neoadjuvant Nivolumab for Upper Tract Urothelial Carcinoma

The NEVOLUTION Study: An Open Label, Single-arm, Phase II Study of Neoadjuvant Nivolumab in Locally Advanced Upper Tract Urothelial Carcinoma

determined by Clavien-Dindo classification

Milestone time points analysis of DFS6, DFS12, DFS 18 and median PFS by investigator assessment per RECIST 1.1

Milestone time points analysis of OS6, OS12, OS18 and median OS by investigator assessment per RECIST 1.1

Ono Pharmaceutical Co. Ltd

YULISU

Assistant Professor-level Attending Physician

Gland and Hormone Related Diseases

Pancreatic Neoplasms

Pancreatic Cancer

Patients experiencing favorable prognosis (defined as RFS≥60 months) following resection for pancreatic adenocarcinoma

Patients experiencing unfavorable prognosis (defined as RFS\<12 months) following resection for pancreatic adenocarcinoma

The study aims at evaluating spatially resolved gene expression profiles of pancreatic and ampullary adenocarcinoma at favorable prognosis after surgical resection, in order to identify molecular features associated to a less aggressive biologic behavior that may benefit from upfront surgery.

Despite technical improvements, surgery for pancreatic adenocarcinoma is still burdened by poor survival outcomes of only 10% at 5 years, due to very high locoregional and distant recurrence rates. In order to improve such disappointing results, several studies are now focusing on the role of neoadjuvant treatment. Recent evidence shows that neoadjuvant treatment may achieve improved intention-to-treat survival outcome, increased rates of margin-negative resections and decreased incidence of lymph node metastases. However, all surgical series report that a limited subset of patients achieve long-term survival following radical surgical resection.

After a systematic review of the available evidence on molecular profiling of pancreatic adenocarcinoma published until today the investigators have undertaken a retrospective study aimed at investigating the presence of possible genetic factors associated to a less aggressive clinical behavior. Clinical, biological and pathological features collected in a prospectively maintained database of radical surgery for pancreatic adenocarcinoma will be retrospectively reviewed together with an analysis of molecular features on surgical samples belonging to patients radically operated at the National Institute of Cancer of Milan. Such features may be used to identify those patients who may benefit from upfront surgery; in such group, vascular resections and reconstructions could be considered more liberally.

The study will consist of 2 phases:

1. A preliminary exploratory phase (group A) based on approximately 20 surgical samples of patients with surgically resected pancreatic adenocarcinoma, not treated by neoadjuvant chemotherapy, in order to evaluate the intrinsic role of tumor biology and avoid the selection of molecular features associated to treatment response. This cohort will consist of 2 groups of 10 patients each with prognostically favorable (RFS≥60 months) and unfavorable tumors (RFS\<12 months), respectively. Patients from the 2 groups will be matched for clinicopathological tumor-related features. Spatially resolved transcriptomic analysis will be performed by the GeoMx Digital Spatial Profiler (DSP) (NanoString Technologies, Seattle, WA, USA) on samples of the two groups and the resulting gene expression profiles will be compared, in order to identify different patterns of gene expression in prognostically different pancreatic adenocarcinomas. Such patterns will also be compared with the TCGA database.
2. A subsequent expanded phase, based on the results of the previous exploration, will take place in case a different gene expression profile is identified. The internal validation set (group B) consists in additional 20 surgical samples associated to favorable and unfavorable prognosis (10 patients each), respectively, belonging to the same institutional series and matched for clinicopathological tumor-related features. RNA-seq analysis will be carried out on these surgical samples, aiming at confirming the results of the exploratory analysis and refine the gene expression profile. In this subset, the enrolment of patients who underwent neoadjuvant treatment will be allowed.

Due to the limited number, samples from patients affected by ampullary adenocarcinoma with favorable prognosis will be analyzed in one step and compared to matched cases with unfavorable prognosis (8 patients each, group C).

Following the identification of gene expression profiles both for pancreatic and ampullary adenocarcinoma, an external validation set will be enrolled in order to perform RNA-seq analysis on additional 60-80 surgical samples from other institutions and validate the prognostic relevance of the identified pattern in predicting a less aggressive disease course.

Gene Expression Profile of Resected Pancreatic and Ampullary Adenocarcinoma at Favorable Prognosis

Identification of Gene Expression Profile Associated With Favorable Prognosis in Patients Undergoing Radical Surgery for Pancreatic and Ampullary Adenocarcinoma

Identification of DSP gene aberrations associated to favorable prognosis (≥60-month RFS) after radical surgery for pancreatic and ampullary adenocarcinoma, through comparison of prognostically favorable and unfavorable gene expression profiles found in different tumor and microenvironment compartments.

Comparison of the gene expression profile found at DSP with the TCGA database in order to confirm the clinical relevance of the identified gene expression pattern associated to prognostically favorable tumors

Identification of clinical, biological and pathological prognostic factors associated to favorable prognosis (≥60-month RFS) after radical surgery for pancreatic adenocarcinoma

External validation of the identified gene expression profile through gene expression analysis of surgical samples from patients undergoing radical surgery for pancreatic adenocarcinoma in a different institution

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Molecular Profiling to Improve Outcome of Patients in Cancer. A Pilot Study	NCT03546127	Colorectal Carc... Soft Tissue Sar...	Next Generation...	18 Years -	Institut National de la Santé Et de la Recherche Médicale, France
Molecular Profiling to Improve Outcome of Patients in Cancer. A Pilot Study	NCT03546127	Colorectal Carc... Soft Tissue Sar...	Next Generation...	18 Years -	Institut National de la Santé Et de la Recherche Médicale, France
Integrative Analysis of Pulmonary Sarcomatoid Carcinoma (PSC)	NCT04215913	Lung Cancer	The investigato...	18 Years - 70 Years	Shanghai 10th People's Hospital
Biomarker Discovery in Patients With Advanced Biliary Tract Cancer	NCT04871321	Biliary Tract C... Cholangiocarcin... Gallbladder Can...	nab-paclitaxel ...	19 Years -	CHA University
Identification of Molecular Biomarkers for Cancer Target Therapy Efficacy	NCT03724097	Cancer	RNA sequencing Transcriptome a... target drug wit... target drug wit... non-target drug palliative care	18 Years - 80 Years	OmicsWay Corp.
Molecular Pathway Activation Markers Predicting Efficacy of Trastuzumab Therapy for HER2-positive Breast Cancer	NCT03521245	HER2-positive B...	RNA sequencing Transcriptome a... Trastuzumab Chemotherapy	18 Years - 80 Years	OmicsWay Corp.
Integrative Analysis of Pulmonary Sarcomatoid Carcinoma (PSC)	NCT04215913	Lung Cancer	The investigato...	18 Years - 70 Years	Shanghai 10th People's Hospital
Predicting Biomarker of Gastric Cancer Chemotherapy Response	NCT03253107	Gastric Cancer Chemotherapy Ef... Predictive Canc...	Chemotherapy	20 Years - 80 Years	Kyungpook National University Hospital
Neoadjuvant Nivolumab for Upper Tract Urothelial Carcinoma	NCT05160285	Upper Urinary T...	Nivolumab 100 M...	20 Years - 85 Years	Chang Gung Memorial Hospital
Gene Expression Profile of Resected Pancreatic and Ampullary Adenocarcinoma at Favorable Prognosis	NCT05754788	Resectable Panc...		18 Years - 80 Years	Fondazione IRCCS Istituto Nazionale dei Tumori, Milano
Clinical Benefit of Using Molecular Profiling to Determine an Individualized Treatment Plan for Patients With High Grade Glioma	NCT03739372	Glioma Glioma of Brain Cancer Pediatric Cance... Pediatric Brain... Astrocytoma Glioblastoma Hemispheric	Specialized tum...	- 21 Years	University of California, San Francisco

Spots Global Cancer Trial Database for rna sequencing