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Fig. 10 DBiT-seq workflow. A fixed tissue slide is stained with a cocktail of antibody-derived DNA tags (ADTs) to label the proteins of interest. Two
set of barcodes are introduced to the tissue slide through a polydimethylsiloxane (PDMS) microfluidic device. Then, the microfluidic chip is
removed, and a 2-D mosaic of barcodes is built on the tissue. The barcoded tissue is imaged under an optical microscope. Finally, cDNA is
extracted, amplified, and built as a sequencing library for NGS sequencing. In silico reconstruction is applied to create a spatial map of mRNA
and protein expression. (Reproduced with permission from Liu Y, et al. High-spatial-resolution multi-omics sequencing via deterministic barcoding in
tissue. Cell 2020.)
320 Yi-Chien Wu et al.
Данная книга находится в списке для перевода на русский язык сайта https://meduniver.com/
individual cells, it may yield data comparable to current scRNA-seq strategies, but with
subcellular resolution. In turn, alternative methods to print barcoded oligo(dT) primers
onto tissue, perhaps informed by the tissue image, may be worthwhile as a way to pursue
spatial multiomic analysis of the TIME.
5. Conclusions and future prospects
Chromogenic IHC and ISH and visual inspection by brightfield microscopy to
image one protein or transcript at a time in thin sections cut from fixed and embedded
tumor biopsy tissue are routinely applied in clinical cancer diagnosis and therapeutic
monitoring. Often combined with clinical findings, these simple assays are sufficient
to distinguish among cancer types and grades, select appropriate therapies, and evaluate
patient response (or resistance). However, the use of chromogenic, single biomarker
assays has not proved satisfactory as a predictive test for approved or investigational
immunotherapies. Deeper profiling of cell composition and biomarker expression in
the TIME and other elements of the tumor and stroma is needed to reveal signatures that
will predict patient response or resistance.
Multiplexed fluorescent immunohistochemistry is increasingly considered a core
approach in immuno-oncology research [62], but current tools are not fully satisfactory
for clinical translation. While multiple technologies are now practical and/or commercialized for multiplexed tissue analysis, few have been validated for analysis of the TIME
and less than a handful have been broadly adopted, even for academic research. Along
with a lack of incentives for adopting new technologies in clinical pathology and the slow
and fitful path toward acceptance of digital pathology, even well-established methods
face considerable challenges on the way to becoming validated and routine clinical tests.
A promising work-around is to exploit deep profiling and AI to identify the features of
the TIME that are most predictive of ICI response or resistance, yielding candidate signatures. Looking forward, once these signatures are identified and validated, clinical
pathologists will embrace targeted methods that measure and map just a few specific protein or transcript biomarkers in tissue long before considering unbiased methods such as
spatial multiomics, despite the clear advantages for deeper profiling. Among current technologies, three- or four-plex chromogenic immunohistochemistry in FFPE is likely sufficient to evaluate these TIME signatures, is readily implemented in any modern
pathology lab and may satisfy current and future clinical needs but its broader use may
help lower barriers to adoption of fully automated, highly multiplexed, multiomic tissue
analysis.
Rather than be concerned with long-term hopes for clinical adoption, it may be more
appropriate to focus short-term on current opportunities for methodological innovation
and technical advances. Improving the speed, signal-to-background, spatial resolution,
and profiling depth of existing methods remains important, particularly for spatial multiomics. Further progress on 3-D protein and RNA detection is needed. The next breakthrough may be sensitive and specific spatial profiling of T and B cell immune receptors at
single-cell resolution in the TIME, a capability that is already being commercialized for
single-cell analysis. With better information on the specificities, spatial distribution, and
activation states of the immune repertoire in a tumor, it may be possible to fully dissect
how immune checkpoint blockade mediates its local effects.
Looking to the future, we can envision minimally invasive sensors that enable an anal-
ysis of multiple markers at cellular resolution in two or three dimensions in real-time and
in situ, bypassing the need for biopsy and tissue processing. As technologies continue to
advance, regular interrogation or even continuous monitoring of the TIME during treatment may enable truly personalized immunotherapy, with the potential to dramatically
change the outlook for cancer in most patients.
Acknowledgments
The authors appreciate support from the NIH, NCI, and NIBIB via R01s CA199663 and CA217182 to
S.J.K. and R00 EB022636 and C06 RR015482 to S.S.L. A licensed copy of Biorender.com was used to
prepare figures. We thank Amy Flor and Evan H. Phillips for editing assistance.
Conflicts of interest
S.J.K. is a cofounder and owner of Cell IDx, a company that develops tools for multiplex immunodetection
in FFPE thin sections. S.J.K. and S.S.L. are cofounders and owners of Transnostics, a company that is
developing T3 as a technology for 3-D immunodetection in tissue.
321Spatial mapping of the tumor immune microenvironment
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