Eco-oncology | Jonathan Lenoir

We would like to advertise a postdoctoral position for 15 months funded by the Hauts-de-France region within the framework of our project PICCell – Predicting biological Invasion, at the interface between invasive speCies and Cancer cells.

Context and main objectives

Though playing out at very different levels of life organization, cancer cells and invasive alien species (IAS) involve similar processes of invasion, growth and spread. Few recent studies at the frontier between ecology and oncology (i.e., eco-oncology) have made the parallel between both disciplines, calling for interdisciplinary research to better understand the mechanisms that underly invasion success of IAS and cancer cells (e.g. Noorbakhsh et al. 2020, Reynolds et al. 2020, Neinavaie et al., 2021). The PICCell project addresses this challenge by combining the expertise of researchers in both invasion ecology and experimental oncology. PICCell relies on the hypothesis that the “construction” of a new ecological niche is a key step towards the successful invasion for cancer cells and IAS. The bilateral objectives of this interdisciplinary project are: (i) to apply IAS invasion ecology approaches to medical oncology in order to better understanding the mechanisms of tumor invasion and to predict the occurrence and distribution of metastases within target organs; (ii) to use the know-how of medical oncology to better understand the construction of the ecological niche generated by the arrival of an IAS; (iii) to initiate research actions in eco-oncology in order to improve our understanding of invasion success and to decipher the Darwinian and random mechanisms that are key to this success. The tasks proposed to meet these objectives consist in: (1) the application of the niche concept and the so-called species distribution models (SDMs) to cancer cells within the micro-environment of key organs (e.g., the pancreas) to predict the spatial distribution of cancer cells given microenvironmental constraints; and (2) the development of a research consortium.

Main tasks

The successful candidate will apply SDMs’ tools to model the realized niche of human pancreatic cancer cells and identify the micro-environmental variables explaining their distributions (definition of an environmental raster) so as to predict the potential distribution of local (primary tumor) and distant (metastasis) cancer cells. His/her main tasks will be:

To ensure an active research survey of academic works and scientific literature at the interface between invasion ecology and experimental oncology;
To coordinate the “upstream” steps of the modelling of the realized niche of cancer cells as a function of micro-environmental conditions (e.g., concentration of elements with cells) within cells of the focal organ (i.e., the pancreas);
To be in charge of collecting biological, clinical, and “micro-environmental” data from the different partners and contributors involved in PICCell. The candidate will work in close collaboration with a Master 2 student to be recruited to collect and process histopathological data (i.e., cancer cell occurrence data as well as data on micro-environmental conditions in the pancreas) from microscope slides in a “spatialized” and contiguous format, such as raster grids as it is typically used in SDMs in ecology (see below for a more detailed list of tasks);
To participate in creating, structuring and moderating the PICCell consortium. The candidate will have a key role in the dialogue between the different partners of the project. She/he will be responsible for identifying and linking their respective skills, thereby anchoring the development of cross-disciplinary issues between ecology and experimental oncology;
To implement the following modelling steps, from “tumour” versus “non-tumour” pancreatic histological sections of human and mouse models:
1. Collect and extract the scenopoetic and bionomic predictive micro-environmental variables obtained from histopathological sections (cf. microscopic slides and pre-processing phase);
2. Calibrate ecological niche models by correlating the relevant micro-environmental variables with the occurrence and absence of tumour cells in the histological sections;
3. Project the probabilistic distributions of cancer cell occurrence across independent sets of histological sections for model validation (cf. assessing model interpolation and extrapolation capabilities);
4. Develop a specific approach to forecast the establishment of metastases in distant organs (i.e., model transferability).
To deliver the modelling work carried out in the form of communications and scientific publications with an international audience;
To impulse a prospective dynamic by using PICCell as a prism to mobilize other partner teams, new ideas and other sources of funding.

Qualifications

A Ph.D. in numerical ecology, ecoinformatics or a related field. The successful applicant will have:

Experience working (or strong interest) on theoretical ecology (familiar with the niche concept);
Experience with statistical and modelling tools applied to spatial ecology (e.g., spatial analysis);
Good programming skills in the R language or equivalent (Python);
Ability to work in a team and interest in interdisciplinarity;
Excellent oral and written English language skills;
Capacity to work autonomously but also collaboratively.

Where

At the UMR CNRS 7058 « Ecologie et Dynamique des Systèmes Anthropisés » (EDYSAN), 80000 Amiens, France.

Starting date and duration

As early as September 4th 2023 and no later than October 2nd 2023. The postdoctoral position is for 15 months.

Gross salary

To be discussed depending on the experience of the successful candidate.

Application instructions

Applicants must submit a cover letter indicating the date that they will be available to begin the position, a curriculum vitae, copies of 2 publications relevant to the call. Applicants should include names and e-mail addresses for two potential referees.

All application materials must be submitted as PDF(s) in a single email by the closing date, on July 21st 2023, to: