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\begin{document}

\title{Live-streamed preprint Journal Club on ``EMT network-based feature
selection improves prognosis prediction in lung adenocarcinoma'' --
October 23, 2018}



\author[1]{Daniela Saderi, Ph.D.}%
\author[2]{Dariusz Murakowski}%
\affil[1]{Oregon Health \& Science University}%
\affil[2]{MIT}%


\vspace{-1em}



  
  \date{May 25, 2024}


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\selectlanguage{english}
\begin{abstract}
This is a review of the bioRxiv preprint ``EMT network-based feature
selection improves prognosis prediction in lung adenocarcinoma'' by
Borong Shao, Maria Bjaan\selectlanguage{ngerman}æs, Åslaug Helland, Christof Schütte, Tim
Conrad,~\href{https://doi.org/10.1101/410472}{doi:10.1101/410472}. This
review was compiled from a discussion during the live-streamed
Bioinformatics preprint journal club as part of an Open Access Week
effort organized by the PREreview team and PLOS. Event details can be
found~\href{https://prereview.org/users/153686/articles/325778-prereview-plos-open-access-week-preprint-journal-club-information}{here},
and the collaborative Etherpad showing all the journal club notes can be
found~\href{https://etherpad.net/p/BioinformaticsLiveStreamedPREJC}{here}.

\par\null

In addition to those named as authors above, the participants who wished
to be acknowledged for their contributions to this review are as
follows: Samantha Hindle, Paul Goetsch, and Bradly Alicea.%
\end{abstract}\selectlanguage{ngerman}%



\sloppy


\section*{Summary}

{\label{742313}}

The goal of this preprint is to demonstrate the utility of using a
phenotype relevant network-based feature selection (PRNFS) framework to
improve prediction of cancer prognosis from multiple sets of
high-dimensional omics data. The proposed network described biological
interactions pertaining to epithelial-to-mesenchymal transition (EMT),
with the goal of improving the prognosis prediction of lung
adenocarcinoma.

\par\null

All participants found the research very interesting and reported that,
for the most part, the results supported the conclusions. However, one
third of the participants reported having problems with understanding
the methods because they appeared incomplete or not sufficiently clear
for another researcher to replicate the findings. The major problem
reported by two thirds of the participants was related to the figures
and tables being hard to read and interpret.

\par\null

\section*{Major comments}

{\label{910645}}

Many journal club participants recognized the importance of the study
and the applicability of the results to research questions beyond cancer
prognosis. Throughout the preprint, the authors make connections between
gene expression networks and phenotypic processes in a novel way using a
variety of methods. Many participants suggested the inclusion of a
figure showing the network and a diagram to help the reader navigate the
comparisons between methods and appreciate the advantages and
improvements of the proposed approach over alternative ones. Given that
the leading author was present during the journal club, we learned that
more details on the network are available on the author's GitHub
repository and the link is in the manuscript -- however, it currently
leads to a 404 page. Given that many readers missed this, it was
suggested that the authors emphasize this more in the manuscript.
Additionally, in order for the GitHub repository to be useful and
accessible, it would help to have a short description of its content in
a README.md page (see
\href{https://guides.github.com/features/wikis/}{GitHub guide}).

Furthermore, it would be helpful for the reader to be able to tease
apart the differences between feature selection alone and classification
methods. For example, this would help address how selecting features
based on the EMT-based phenotype GRN would improve predictions compared
to random signature. One participant suggested using a framework
developed by \citet{Venet_2011} to rapidly assess comparisons between
networks and validate improvements of one over another.

\par\null

Other comments from the participants were also related to suggesting
ways to improve the readability of the manuscript and help readers to
more easily understand the main takeaways of the results. For example,
it was suggested that the authors combined Figures S5, S6, S7 into one
figure with three panels for a more direct comparison between GE+DM and
GE or DM independently. For similar reasons, it was also suggested to
select a fewer number of ``essential'' figures and tables for the main
manuscript, and move the remaining figures and tables to supporting
information. Additional suggestions are listed below.

\par\null

\section*{Minor comments, suggestions, and
typos}

{\label{755748}}

\begin{itemize}
\tightlist
\item
  It would be useful to add a paragraph to the Discussion highlighting
  (1) how this approach could be utilized to better target a set of
  prognostic markers from patient samples and (2) the potential
  generalization of this approach to other cancers.~
\item
  To avoid ambiguity, it would be better to use ``AUROC'' or ``ROCAUC''
  instead of just ``AUC''. Moreover, this abbreviation and ``AUPR ''
  should be defined at their first usage (line 185). ``ROC-PR'' should
  be ``AUPR.''
\item
  TCGA LUAD data should be cited according~ to
  \href{http://gdac.broadinstitute.org/runs/info/DOIs__stddata.html}{guidelines
  given by the Broad Institute}.
\item
  For a network visualization, the
  \href{http://www.htmlwidgets.org/showcase_networkD3.html}{networkD3
  package in R}~is very useful.
\item
  To improve readability of the preprint, it would be helpful to (1)
  print the supplementary table numbers and/or captions directly above
  their corresponding table contents, and (2) print the figure numbers
  on the same page as each figure (pages 20-30).
\item
  Depending on the style guide, Ref. 37 should state that it is a PhD
  dissertation. It would also be helpful to refer to specific chapters
  or even sections.
\item
  NetRank should have a capitalized R throughout.
\item
  The authors should clarify how the EMT features were binarized using
  their means (line 280).
\item
  The authors should clarify which steps were performed elsewhere and
  which were performed for this manuscript. For example,
  they~\emph{previously} ``tested the EMT signatures'' (line 344).
\item
  Minor editing and proofreading by a generalist reader would be
  helpful. Some examples are listed below:
\item
  Line 4 typo: caner --\textgreater{} cancer~
\item
  Line 9 typo: details --\textgreater{} detail
\item
  Line 132 typo: being --\textgreater{} are
\item
  Line 137 typo:~should use a semicolon, as in ``samples; we thus''
\item
  Line 139: should be 74, 455, 123 nodes, respectively
\item
  Lines 206-207: ``association rule mining'' can be cited earlier than
  line 269. Some of the details of this approach are currently found in
  the Results section; they may be more appropriate in the Experiments
  and/or Introduction sections.
\item
  Line 282: textit should be preceded by \textbackslash{} in the
  (presumably LaTeX) source code
\item
  Lines 288-304: the interpretation of these rules would benefit from
  citations supporting the ``established findings in cancer research''~
\end{itemize}

\par\null

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